Category Archives: Biology

Biology

Bending the Rules of Biology: Stanford Scientists Unveil Cellular Origami in Microscopic Predators – SciTechDaily

A side-by-side comparison of Lacrymaria olor, a remarkable ciliate with its neck extended and retracted. Researchers discovered origami-like folds make this morphing possible where microtubules define folding pleats. Credit: Prakash Lab

Stanford scientists have unveiled lacrygami, a phenomenon where Lacrymaria olor extends its structure dramatically, influenced by its cytoskeletal design, promising advances in microscopic technology.

There are some things in life you can watch and then never unwatch, said Manu Prakash, associate professor of bioengineering at Stanford University, calling up a video of his latest fascination, the single-cell organism Lacrymaria olor, a free-living protist he stumbled upon playing with his paper Foldscope. Its just its mesmerizing.

From the minute Manu showed it to me, I have just been transfixed by this cell, said Eliott Flaum, a graduate student in the curiosity-driven Prakash Lab. Prakash and Flaum spent the last seven years studying Lacrymaria olors every move and recently published a paper on their work in the journal Science.

The first time I came back with a fluorescence micrograph, it was just breathtaking, Flaum said. That image is in the paper.

The video Prakash queued up reveals why this organism is much more than a pretty picture: a single teardrop-shaped cell swims in a droplet of pond water. In an instant, a long, thin neck projects out from the bulbous lower end. And it keeps going. And going. Then, just as quickly, the neck retracts back, as if nothing had happened.

In seconds, a cell that was just 40 microns tip-to-tail sprouted a neck that extended 1500 microns or more out into the world. It is the equivalent of a 6-foot human projecting its head more than 200 feet. All from a cell without a nervous system.

It is incredibly complex behavior, Prakash said with a smile.

L. olor is featured in the journal Science because Prakash and Flaum have discovered in this behavior a new geometric mechanism previously unknown in biology. And they are the first to explain how such a simple cell can produce such incredible morphodynamics, beautiful folding and unfolding aka origami at the scale of a single cell, time and again without fail.

It is geometry. L. olors behavior is encoded in its cytoskeletal structure, just like human behavior is encoded in neural circuits.

This is the first example of cellular origami, Prakash said. Were thinking of calling it lacrygami.

Specifically, it is a subset of traditional origami known as curved-crease origami. It is all based on a structure of thin, helical microtubules ribs that wrap inside the cells membrane. These microtubule ribs are encased in a delicate diaphanous membrane, defining the crease pattern of peaks in a series of mountain-and-valley folds.

Prakash and Flaum used transmission electron microscopy and other state-of-the-art investigatory techniques to show there are actually 15 of these stiff, helical microtubule ribbons enshrouding L. olors cell membrane a cytoskeleton. These tubules coil and uncoil, leading to long projection and retraction, nesting back into themselves like the bellows of a compressed helical accordion. The gossamer of membrane tucks away inside the cell in neat, well-defined pleats.

When you store pleats on the helical angle in this way, you can store an infinite amount of material, Flaum explained. Biology has figured this out.

The elegance is in the arithmetic. It is mathematically impossible for this structure to unfold in any other way and, conversely, only one way it can retract. What is perhaps more striking to Prakash is the robustness of the architecture. In its lifetime, L. olor will perform this projection and retraction 50,000 times without flaw. He said: L. olor is bound by its geometry to fold and unfold in this particular way.

The key is an under-studied mathematical phenomenon occurring at the precise point where the ribs twist and the folded membrane begins to unfurl. It is a singularity a point where the structure is folded and unfolded at the same time. It is both and neither singular.

Grabbing a piece of paper, Prakash folds it into a cone shape and then pulls on one corner of the paper to demonstrate how this singularity (called d-cone) travels across the sheet in a neat line. And, by pushing back on the corner how the singularity travels back the exact same path to its original position.

It unfolds and folds at this singularity every time, acting as a controller. This is the first time a geometric controller of behavior has been described in a living cell. Prakash explained.

A constant theme running throughout the Prakash Labs work is a profound sense of wonder and playfulness that results in the energetic curiosity necessary to pursue such an idea for such a long time. It is, to put it in Prakashs terms, old-school science. He also refers to it as recreational biology.

To demonstrate his inspiration, Prakash displayed a family tree of other single-celled organisms that he has chosen to study. True, none can do what L. olor can do, he said. But these intricate geometries come in thousands of forms. Beautiful? Certainly, but each is also hiding wonderful and unwritten rules under their sleeves.

We started with a puzzle, Prakash explained with all the seriousness a scientist can muster. Ellie and I asked a very simple question: Where does this material come from? And where does it go? As our playground, we chose Tree of Life. Seven years later, here we are.

As for practical applications, Prakash the engineer is already imagining a new era of deployable microscale living machines that could transform everything from space telescopes to miniature surgical robots in the operating room.

Reference: Curved crease origami and topological singularities enable hyperextensibility of L. olor by Eliott Flaum and Manu Prakash, 7 June 2024, Science. DOI: 10.1126/science.adk5511

Prakash is also a senior fellow at the Stanford Woods Institute for the Environment, associate professor (by courtesy) of biology and of oceans, a member of Stanford Bio-X, the Wu Tsai Human Performance Alliance, the Maternal & Child Health Research Institute, and the Wu Tsai Neurosciences Institute.

This research was funded by the National Institutes of Health, the National Science Foundation, the Moore Foundation, the Howard Hughes Medical Institute, the Schmidt Foundation, and the Chan Zuckerberg Biohub San Francisco. Some of this work was performed at the Cell Sciences Imaging Facility at Stanford.

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Bending the Rules of Biology: Stanford Scientists Unveil Cellular Origami in Microscopic Predators - SciTechDaily

Biology

Popular Theory Debunked: Scientists Identify Unexpected Drivers Behind Giraffes’ Long Necks – SciTechDaily

A Penn State study suggests that giraffes long necks may have evolved due to the high nutritional needs of females, who require deep foraging into trees for food. While the necks-for-sex hypothesis posits that male competition drove neck length evolution, findings show females have proportionally longer necks. This research, published in Mammalian Biology, highlights the importance of conserving giraffe habitats to support their unique ecological needs.

Why do giraffes have long necks? A new study by biologists from Penn State examines the evolutionary development of this distinctive feature, providing fresh insights into a classic question. While the prevailing theory attributes the long necks to male competition, the researchers observed that female giraffes actually have proportionally longer necks compared to males. This suggests that the high nutritional demands of females might have been a key factor in the evolution of the giraffes long neck.

The study, which explored body proportions of both wild and captive giraffes, is described in a paper that was recently published in the journal Mammalian Biology. The findings, the team said, indicate that neck length may be the result of females foraging deeply into trees for otherwise difficult-to-reach leaves.

In their classic theories of evolution, both Jean Baptiste Lamarck and Charles Darwin suggested that giraffes long necks evolved to help them reach leaves high up in a tree, avoiding competition with other herbivores. However, a more recent hypothesis called necks-for-sex suggests that the evolution of long necks was driven by competition among males, who swing their necks into each other to assert dominance, called neck sparring. That is, males with longer necks might have been more successful in the competition, leading to reproducing and passing their genes to offspring.

The necks-for-sex hypothesis predicted that males would have longer necks than females, said Doug Cavener, Dorothy Foehr Huck and J. Lloyd Huck Distinguished Chair in Evolutionary Genetics and professor of biology at Penn State and lead author of the study. And technically they do have longer necks, but everything about males is longer; they are 30% to 40% bigger than females. In this study, we analyzed photos of hundreds of wild and captive Masai giraffes to investigate the relative body proportions of each species and how they might change as giraffes grow and mature.

Although male and female giraffes have the same body proportions at birth, they are significantly different as they reach sexual maturity. Females have proportionally longer necks and longer bodies than males, which might help with foraging and child-rearing, while males have wider necks and longer front legs, which might help win fights against other males and with mating. Credit: Penn State

The researchers gathered thousands of photos of captive Masai giraffes from the publicly accessible photo repositories Flickr and SmugMug as well as photos of wild adult animals that they have taken over the past decade. Because absolute measurements like overall height are difficult to determine from a photograph without a point of reference of known length, the researchers instead focused on measurements relative to one another, or body proportions for example, the length of the neck relative to the entire height of the animal. They restricted their analysis to images that met strict criteria, such as only using images of giraffes perpendicular to the camera, so they could consistently take a variety of measurements.

We can identify individual giraffes by their unique spot pattern, Cavener said. Thanks to the Association of Zoos and Aquariums, we also have the full pedigree, or family tree, of all Masai giraffes in North America in zoos and wildlife parks, as well as their birthdates and transfer history. So, by carefully considering this information, when the photo was taken and the approximate age of the animal, we could identify the specific individual in nearly every photo of a captive giraffe. This information was critical to understanding when male and female giraffes start to exhibit size differences and whether they grow differently.

At birth, male and female giraffes have the same body proportions. The researchers found that, although males generally grow faster in the first year, body proportions are not significantly different until they start to research sexual maturity around three years of age. Because body proportions change early in life, the team limited their study of wild animals whose ages are largely unknown to fully grown adults.

In adult giraffes, the researchers found that females have proportionally longer necks and trunks or the main section of their body, which does not include legs or the neck and head. Adult males, on the other hand, have longer forelegs and wider necks. This pattern was the same in both captive and wild giraffes.

Rather than stretching out to eat leaves on the tallest branches, you often see giraffes especially females reaching deep into the trees, Cavener said. Giraffes are picky eaters they eat the leaves of only a few tree species, and longer necks allow them to reach deeper into the trees to get the leaves no one else can. Once females reach four or five years of age, they are almost always pregnant and lactating, so we think the increased nutritional demands of females drove the evolution of giraffes long necks.

The researchers noted that sexual selection either competition among males or preference among females for larger mates was likely responsible for the overall size difference between males in females, as is the case in many other large, hoofed mammals that are polygynous where one male mates with many females. They suggest that, following the evolution of the long neck, sexual selection including male body pushing and neck sparring behaviors may have contributed to males wider necks. Additionally, the longer forelegs of males may assist in mating, which the researchers said is a brief and challenging affair that is rarely observed.

Interestingly, giraffes are one of few animals whose height we measure to the top of the head like humans rather than to their withersthe highest part of the back, like in horses and other livestock, Cavener said. The female has a proportionally longer axial skeleton a longer neck and trunk and are more sloped in appearance, while the males are more vertical.

The research team is also using genetics to identify relationships in groups of wild giraffes to better understand which males are successful at breeding. The goal is to shed additional light on mate choice and sexual selection, as well as guide conservation efforts for this endangered species.

If female foraging is driving this iconic trait as we suspect, it really highlights the importance of conserving their dwindling habitat, Cavener said. Populations of Masai giraffes have declined rapidly in the last 30 years, in part due to habitat loss and poaching, and it is critical that we understand the key aspects of their ecology and genetics in order devise the most efficacious conservation strategies to save these majestic animals.

Reference: Sexual dimorphisms in body proportions of Masai giraffes and the evolution of the giraffes neck by Douglas R. Cavener, Monica L. Bond, Lan Wu-Cavener, George G. Lohay, Mia W. Cavener, Xiaoyi Hou, David L. Pearce and Derek E. Lee, 3 June 2024, Mammalian Biology. DOI: 10.1007/s42991-024-00424-4

In addition to Cavener, the research team at Penn State includes Monica Bond, academic affiliate of biology; Lan Wu-Cavener, academic affiliate of biology; George Lohay, a postdoctoral researcher at the time of the research who is now at the Grumeti Fund; Mia Cavener, a graduate student at the time of the research; Xiaoyi Hou, graduate student in the Molecular, Cellular, and Integrative Biosciences program; David Pearce, an undergraduate student at the time of the research; and Derek Lee, academic affiliate of biology.

Funding from Penn State, the Penn State Huck Institutes of the Life Sciences and the Wild Nature Institute supported this research.

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Popular Theory Debunked: Scientists Identify Unexpected Drivers Behind Giraffes' Long Necks - SciTechDaily

Biology

Changes Upstream: RIPE team uses CRISPR/Cas9 to alter photosynthesis for the first time – EurekAlert

image:

A RIPE team used CRISPR/Cas9 to increase gene expression in rice by changing its upstream regulatory DNA. While other studies have used the technology to knock out or decrease the expression of genes, their research is the first unbiased gene-editing approach to increase gene expression and downstream photosynthetic activity.

Credit: RIPE Project

A team from the Innovative Genomics Institute at the University of California, Berkeley (UCB) has produced an increase in gene expression in a food crop by changing its upstream regulatory DNA. While other studies have used CRISPR/Cas9 gene-editing to knock out or decrease the expression of genes, new research published in Science Advances is the first unbiased gene-editing approach to increase gene expression and downstream photosynthetic activity.

Tools like CRISPR/Cas9 are accelerating our ability to fine-tune gene expression in crops, rather than just knocking out genes or turning them off. Past research has shown that this tool can be used to decrease expression of genes involved in important trade-offs, such as those between plant architecture and fruit size, said Dhruv Patel-Tupper, lead author on the study and former postdoctoral researcher in the Niyogi Lab at UCB. This is the first study, to our knowledge, where we asked if we can use the same approach to increase the expression of a gene and improve downstream activity in an unbiased way.

Unlike synthetic biology strategies that use genes from other organisms to improve photosynthesis, the genes involved in the photoprotection process are naturally found in all plants. Inspired by a 2018 Nature Communications paper that improved the water-use efficiency of a model crop by overexpressing one of these genes, PsbS, in plants, the Niyogi lab, and its leader Kris Niyogi, wanted to figure out how to change the expression of a plants native genes without adding foreign DNA. According to the Food and Agriculture Organization, rice supplies at least 20% of the worlds calories, and because it has only one copy of each of the three key photoprotection genes in plants, it was an ideal model system for this gene editing study.

The Niyogi lab pursued this work as part of Realizing Increased Photosynthetic Efficiency (RIPE), an international research project led by the University of Illinois that aims to increase global food production by developing food crops that turn the suns energy into food more efficiently with support from the Bill & Melinda Gates Foundation, Foundation for Food & Agriculture Research, and U.K. Foreign, Commonwealth & Development Office.

The labs plan was to use CRISPR/Cas9 to change the DNA upstream of the target gene, which controls how much of the gene is expressed and when. They wondered if making those changes would have an impact on downstream activity and by how much. Even they were surprised at the results.

The changes in the DNA that increased gene expression were much bigger than we expected and bigger than weve really seen reported in other similar stories, said Patel-Tupper, now an AAAS Science and Technology Policy Fellow at the USDA. We were a little bit surprised, but I think it goes to show how much plasticity plants and crops have. Theyre used to these big changes in their DNA from millions of years of evolution and thousands of years of domestication. As plant biologists, we can leverage that wiggle room to make large changes in just a handful of years to help plants grow more efficiently or adapt to climate change.

In this study, RIPE researchers learned that inversions, or flipping of the regulatory DNA, resulted in increased gene expression of PsbS. Unique to this project, after the largest inversion was made to the DNA, the team members conducted an RNA sequencing experiment to compare how the activity of all genes in the rice genome changed with and without their modifications. What they found was a very small number of differentially expressed genes, much smaller than similar transcriptome studies, suggesting their approach did not compromise the activity of other essential processes.

Patel-Tupper added that while the team showed that this method is possible, its still relatively rare. Around 1% of the plants they generated had the desired phenotype.

We showed a proof-of-concept here, that we can use CRISPR/Cas9 to generate variants in key crop genes and get the same leaps as we would in traditional plant breeding approaches, but on a very focused trait that we want to engineer and at a much faster timescale, said Patel-Tupper. Its definitely more difficult than using a transgenic plant approach, but by changing something that is already there, we may be able to preempt regulatory issues that can slow how quickly we get tools like this into the hands of farmers.

Experimental study

Not applicable

Multiplexed CRISPR/Cas9 mutagenesis of rice PSBS1 non-coding sequences for transgene-free overexpression

7-Jun-2024

The researchers do not report any conflicting interests.

Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.

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Changes Upstream: RIPE team uses CRISPR/Cas9 to alter photosynthesis for the first time - EurekAlert

Biology

Genome-wide meta-analyses of restless legs syndrome yield insights into genetic architecture, disease biology and … – Nature.com

Ethics statement

All studies were approved by the respective local ethical committees, and all participants provided informed consent. The EU-RLS-GENE study was approved by an institutional review board at the University Hospital of the Technical University of Munich (2488/09). The INTERVAL dataset was approved by the National Research Ethics Service Committee East of EnglandCambridge East (REC 11/EE/0538). Participants of 23andMe provided informed consent under a protocol approved by the external AAHRPP-accredited IRB, Ethical and Independent (E&I) Review Services. As of 2022, E&I Review Services is part of Salus IRB (https://www.versiticlinicaltrials.org/salusirb). The deCODE dataset was approved by the National Bioethics Committee of Iceland. The Danish Blood Donor Study (DBDS) dataset was approved by the Scientific Ethical Committee of Central Denmark (M-20090237) and by the Danish Data Protection agency (30-0444). GWAS studies in the DBDS were approved by the National Ethical Committee (NVK-1700407). The Emory dataset was approved by an institutional review board at Emory University, Atlanta, GA, USA (HIC ID 133-98).

Some of the samples were included already in our previous GWAS meta-analysis3. The reported sample numbers are the final sample numbers after quality control. Additional details are provided in the Supplementary Note.

RLS cases were recruited in specialized outpatient clinics for movement disorders and in sleep clinics in European countries (Austria, Czech Republic, Estonia, Finland, France, Germany and Greece), Canada (Quebec) and the USA. RLS was diagnosed in a face-to-face interview by an expert neurologist or sleep specialist based on IRLSSG diagnostic criteria1. Controls were either population-based unscreened controls (Austria, Estonia, Finland, France, Germany) or healthy individuals recruited in hospitals (Canada, Czech Republic, Greece, USA). A total of 6,228 cases and 10,992 ancestry-matched controls had been genotyped on the Axiom array and were the study sample used in our previous meta-analysis. For the current study, 1,020 cases and 8,810 ancestry-matched controls were added who were genotyped on the Infinium Global Screening Array-24 version 1.0. Genotype calling was performed in GenomeStudio 2.0 according to the GenomeStudio Framework User Guide, and identical quality-control criteria were used for both datasets. Imputation was performed on the UK10K haplotype and 1000 Genomes Phase 3 reference panel using the EAGLE2 (version 2.0.5) and PBWT (version 3.1) imputation tools as implemented in the Sanger imputation server. Imputed SNPs with pHWE1105 or an INFO score <0.5 were filtered out.

The INTERVAL study includes whole-blood donors recruited in England between 2012 and 2014. The Cambridge-Hopkins Restless Legs questionnaire was used to define RLS cases, and probable and definite cases were combined to form a binary phenotype as described previously3. A detailed description of Axiom Biobank array genotyping and the imputation procedure plus related quality control in the INTERVAL trial can be found elsewhere34. Briefly, imputation was performed using a joint UK10K and 1,000 Genomes Phase 3 (May 2013 release) reference panel via the Sanger imputation server, and variants with MAF0.1% and INFO score0.4 were retained for analysis.

This study includes research participants of 23andMe who agreed to participate in research studies. The RLS phenotype was defined by self-reported responses to survey questions that assessed whether someone had ever been diagnosed with RLS or had ever received treatment for RLS as described previously3. Participants were genotyped on one of five platforms, all using Illumina arrays with added custom content (HumanHap550+ BeadChip, OmniExpress+ BeadChip, Infinium Global Screening Array). Participant genotype data were imputed in a two-step procedure using a reference panel created by combining the May 2015 release of the 1000 Genomes Phase 3 haplotypes with the UK10K imputation reference panel. Pre-phasing was carried out using either the internally developed tool Finch, which implements the Beagle algorithm, or EAGLE2. Imputation was performed with Minimac3.

This cohort includes only individuals who had not been part of the 23andMe GWAS used in the discovery meta-analysis. Cases and controls were defined as described above.

Individuals in this cohort do not overlap with samples included in the INTERVAL GWAS used in the discovery meta-analysis. RLS status was assessed with a single question on having received a diagnosis of RLS.

For 23andMe and INTERVAL, genotyping and imputation was carried out as described for the discovery stage.

This dataset included the DBDS, a cohort from deCODE Genetics, Iceland, the Emory Hospital Atlanta, USA and the Donor InSight-III study. Phenotyping and genotyping procedures have been described in detail previously4.

First, the Axiom- and the GSA-genotyped datasets were analyzed separately using SNPTEST version 2.5.4 with genotype dosages and assuming an additive model. Age, sex and the first ten PCs from the MDS analysis in PLINK were included as covariates. These summary statistics of the two datasets were then combined by fixed-effect inverse-variance meta-analysis (STERR scheme) using METAL (release 2011-03-25)35. One round of genomic control was performed in each dataset before meta-analysis.

Assuming an additive genetic model, genotype dosages were analyzed in SAIGE (0.35.8.8) using a linear mixed model to account for cryptic relatedness and saddle point approximation to account for casecontrol imbalance36. Age, sex and the first ten PCs of ancestry were included as potential genomic confounders. The analysis was restricted to genetic variants with MAF0.001, INFO0.4 and a minor allele count of 10.

Association analysis was conducted by logistic regression (LRT) assuming additive allelic effects and imputed dosages. Age, sex, genotyping platform and the first ten PCs were included as covariates.

In all individual GWAS, sex-specific analyses were performed using the same pipelines as those for the pooled analyses minus adjustment for sex as a covariate.

We applied the same methods for both the pooled and the sex-specific GWAS. The three independent datasets were combined in a multivariate GWAS meta-analysis using the N-weighted-GWAMA R function (version 1.2.6)37. To assess the possibility of heterogeneity of SNP effects between the studies, Cochrans Q-test was applied as described in METAL.

Data for the X chromosome were available in two of the discovery-stage datasets: EU-RLS-GENE and 23andMe.

For the pooled association analysis, male genotypes were coded as 0/2 (assuming no dosage compensation in males). All other methods were identical to those of the autosomal analyses. In sex-stratified analyses, males were coded as 0/1 and females as 0/1/2.

In both pooled and sex-stratified analyses, males were coded as 0/2 and females as 0/1/2.

Pooled and sex-specific meta-analyses were performed using the N-GWAMA R function as in the autosomal analysis. Because N-GWAMA operates with Z scores, the type of male allele coding did not affect the results.

We performed sex-specific (male-only and female-only) meta-analyses of the corresponding GWAS using the N-GWAMA approach as described above. The results were used to estimate sex-specific heritability and genetic correlation between the sexes.

To detect sex-specific effects, we tested all independent (r2<0.2) genome-wide significant SNPs of the pooled and sex-specific meta-analyses for heterogeneity of effect sizes between the two sexes using Cochrans Q-test (one-sided) and a Bonferroni-corrected significance threshold of Padj0.05/221.

For 23andMe and INTERVAL, quality control and statistical analysis were performed as described for the discovery stage. Statistical analysis for the DBDS, deCODEEmory and Donor Insight studies has been described previously4. Meta-analysis was performed using Han and Eskins random-effects model in METASOFT (RE2, METASOFT version 2.0.1)38.

To define independent risk loci, we first used the --clump command in PLINK (version 1.90b6.7)39 to collapse multiple genome-wide significant association signals based on linkage disequilibrium (LD) and distance (clump-r2>0.05, clump-kb<500kb clump-p1<5108, clump-p2p-value<105). We then performed conditional analyses to identify secondary independent signals in risk loci using GCTA (version 1.93.0beta) with the -cojo-slct option, the P-value threshold for genome-wide significance set at 5108, the distance window set at 10Mb and the colinearity cutoff set at 0.9 (ref. 40). LD was derived from EU-RLS-GENE genotype data. Independent genome-wide significant signals were merged into one genomic risk locus if either their LD block distance was <500kb or their clumped regions were overlapping.

Heritability is reported on the liability scale unless otherwise indicated. Prevalence estimates were derived from the population cohorts INTERVAL and 23andMe themselves. For the EU-RLS-GENE casecontrol dataset and for the meta-analysis, prevalence estimates were derived from previous publications on European ancestries.

We estimated SNP-based heritability under several different heritability models. LDSC (version 1.0.1) was used with standard settings, invoking a model where SNPs with different MAFs are expected to contribute equally to heritability41. LDAK (version 5.0) was used with standard settings to implement the LDAK model, where SNP contributions depend on LD structure and MAF as well as the BLD-LDAK and BLD-LDAK+Alpha models, which incorporate additional annotation-based features42. All analyses were based on summary statistics and filtering according to LDSC default settings, that is, HapMap3 non-HLA SNPs with MAF>0.01 and INFO0.9. The Akaike information criterion of each of these models was reported for model comparison. Further details are provided in the Supplementary Note.

For X chromosome heritability estimation, we followed the approach described by Lee et al. and used the summary statistics of the N-GWAMA meta-analysis43. For sex k, the SNP heritability ({h}_{k}^{2}) relates to the expected 2 statistics as ({mathbb{E}}({chi }_{k}^{2})approx 1+{N}_{k}{h}_{k}^{2}/{M}_{{rm{eff}}}), where Nk is the GWAS sample size, and Meff is the effective number of loci within the examined genomic region (assumed to be the same in males and females). For calculation of the (sex-specific) relative heritability contribution of the X chromosome, 2 statistic-based h2 was also calculated for the autosomes.

For autosomal data, genetic correlations were calculated using LDSC (version 1.0.1) using the same SNP filtering criteria and the two-step estimation option as in the heritability estimation. Because the LDSC framework is not applicable for chromosome X, the genetic correlation coefficient ({hat{r}}_{rm{g}}) was estimated as ({hat{r}}_{rm{g}}=,frac{widehat{{Z}_{rm{m}}{Z}_{rm{f}}}}{sqrt{(;{hat{chi }}_{rm{f},}^{2}-,1)(;{hat{chi }}_{rm{m},}^{2}-,1)}}), where Z and 2 are the Z scores and mean 2 estimates from the female (f) and male (m)-specific studies.

In addition to between-study and between-sex genetic correlations, we performed a large-scale genetic correlation screen for RLS (represented by the pooled autosomal meta-analysis data) and other traits using LDSC as described above. Sources and filtering criteria for summary statistics included in this screen are provided in the Supplementary Note.

Traits significantly correlated with RLS (FDR<0.05, one-sample two-sided Z-test) were taken forward to a bi-serial genetic correlation analysis. Here, we computed the pairwise ({hat{r}}_{rm{g}}) between all traits.

An unsigned weighted correlation matrix was built using the pairwise ({hat{r}}_{rm{g}}) and used as input for a weighted correlation matrix analysis to perform hierarchical clustering and to detect modules with the WGCNA package (version 1.69)44. The following settings were applied in WGCNA: softPower, 6; network type, unsigned; TOMDenom, min; Dynamic-cutree, method=hybrid; deepSplit, 2; minModuleSize, 30; pamStage, TRUE; pamRespectsDendro, FALSE; useMedoids, FALSE. The defining trait categories in each module were determined by consensus through independent review of the within-module cluster structure by visual inspection of network plots at two sites (Helmholtz and Cambridge).

To select traits for MR, we defined two to eight clusters in a module based on its complexity. In each cluster, the traits were ranked according to the significance of their correlation with RLS, and we selected the most significantly correlated medical conditions or potentially modifiable lifestyle factors. We supplemented this list with traits for which an association with RLS has been described in the literature.

Using R version 4.0.4, we filtered GWAS datasets to uncorrelated SNPs (r2<0.01 in the European 1000 Genomes Phase 3 data), aligned them to GRCh37 and mapped them to dbSNP 153 with the gwasvcf package (version 0.1.0). We harmonized effect alleles across studies using the TwoSampleMR package (version 0.5.6)45. Palindromic variants with ambiguous allele frequencies and those with unresolved strand issues were excluded from analysis.

To avoid violations of the classical MR assumptions when studying correlated and likely pleiotropic traits, we used a robust method for bidirectional MR, LHC-MR (version 0.0.0.9000)32. Traits with low heritability (h2<2.5%, ({P_{h^2}})>0.05) were excluded from the analysis. Significance of directionality and confounding effect were tested by comparing the goodness of fit of six degenerate LHC-MR models (only latent effect, only causal effect, only causal effect to RLS, only causal effect from RLS, no causal effect to RLS and no causal effect from RLS) to the full model. We supplemented these analyses with those based on the IVW and MR-Egger methods.

All analyses were performed on the N-GWAMA results of the pooled meta-analysis. We applied several complementary approaches to prioritize candidate genes in the genome-wide significant risk loci. These included the gene-prioritization pipeline of DEPICT (version 1.rel194), three prioritization workflows (positional, eQTL-based and topology-based mapping) provided on the FUMA platform (https://fuma.ctglab.nl/, version 1.3.6a), a gene-level GWAS using MAGMA version 1.08, a transcriptome-wide association study using S-PrediXcan and S-MultiXcan (MetaXcan package version 0.7.4), a colocalization analysis with eCAVIAR (version 2.2) and statistical fine-mapping with CAVIARBF (version 0.2.1)46,47,48,49,50,51,52. In the DEPICT, FUMA eQTL-based mapping, MAGMA and transcriptome-wide association study analyses, a gene was considered prioritized if it had an FDR <0.05; in FUMA topology-based mapping, if it had an FDR <1105; and in eCAVIAR, if it had a colocalization posterior probability >0.1. In FUMA positional mapping, a gene was considered prioritized if genome-wide significant SNPs physically mapped to it. In statistical fine-mapping, a gene was considered prioritized if an SNP in the 95% credible set of the risk locus could be linked to it by either eQTL, chromatin interaction or positional mapping. In addition, we checked whether a gene contained genome-wide significant coding variants (the gene was considered prioritized if it did) and whether a gene mapped to a gene set that was significant in our enrichment analyses (the gene was considered prioritized if it did). We combined the results of all approaches per gene in a prioritization score by summing up the individual results, counting not prioritized as 0 and prioritized as 1. Further details are provided in the Supplementary Note.

We ran DEPICT to detect enrichment of gene sets across risk loci as well as to identify tissue and cell types where expression is enriched for genes across risk loci. We set the significance thresholds for lead SNPs at 1105 and at 5104 for null GWAS; all other settings were the same as those used for gene prioritization (see above). DEPICT was run with all built-in datasets. eQTL mapping and functional prioritization were evaluated in DEPICTs built-in eQTL and reconstituted gene sets.

Excluding 12 SNPs not reaching genome-wide significance in the joint analysis of discovery and validation did not change the main results (Supplementary Table 25).

MAGMA (version 1.08) was used to perform gene set enrichment testing for pathway identification. MAGMA conducts competitive gene set tests with correction for gene size, variant density and LD structure. A total of 7,522 gene sets representing the GO biological process ontology (MSigDB version 7.1, C5 collection, GO:BP subset) were tested for association. We adopted a significance threshold of FDR<0.05 (one-sided t-test).

Using the settings described above, we tested enrichment of RLS heritability with DEPICT across 209 different tissue types covered in the built-in dataset. For an independent validation on the tissue level as well as for the analyses on the cell type level, we mainly used the CELLEX and CELLECT tools53. CELLECT provides two different gene-prioritization approaches for heritability enrichment testing, S-LDSC and MAGMA covariate analysis54,55. For compatibility of the results, the summary statistics of the pooled N-GWAMA analysis were filtered using settings identical to those in our LDSC heritability analyses. Following the recommendations by Timshel et al.53, we applied a tiered approach by starting with body-wide datasets and then focusing on CNS-centric datasets. We used CELLECT software (version 1.3.0) with default settings but updated to MAGMA version 1.08 to test enrichment of RLS heritability in cell type- or tissue-specific genes for datasets with publicly available RNA-seq data. These analyses require a measure of expression specificity for each gene in a cell or tissue type. We either used CELLEX (version 1.2.1) to compute expression specificity or relied on precomputed CELLEX expression specificity scores. Human adult datasets without publicly available raw RNA-seq data were analyzed using MAGMA_Celltyping (version 2.0.0) in top10 mode. The list of input datasets is provided in the Supplementary Note, and results of our evaluation of both approaches showing high correlation are presented in Supplementary Fig. 1 and Supplementary Table 26.

We applied three types of models for genetic risk evaluation and RLS risk prediction: GLM with and without interaction terms, RF models and DNN models. These were implemented as binary classifiers as well as time-to-event classifiers.

Training of the models and evaluation by tenfold cross-validation were based on the EU-RLS-GENE Axiom subset. Therefore, we first conducted a meta-analysis excluding this dataset to generate unbiased summary statistics to be used in all models. Because GWAS have an ascertainment bias, we constructed a simulation cohort dataset by resampling of the EU-RLS-GENE Axiom subset based on the year of birth of the sampled individuals, their ages at onset and the demographic composition of the German population (Supplementary Note). We calculated the PRS using dosages of 216 independent lead SNPs of our discovery meta-analyses.

For a baseline comparison of the predictive power of this score to a PRS based on genome-wide data, we calculated a genome-wide PRS using the LDpred2-auto option of LDpred2 (R package bigsnpr version 1.12.2)56. Variants and the LD reference panel were based on the HapMap3 EUR dataset, and window size for calculating SNP correlation was set to 3cM.

Binary classification models were evaluated by Nagelkerkes pseudo-R2, receiver operator characteristic AUC and precisionrecall AUC. A 5-year binary classifier was constructed for each of the time-to-event models by predicting the label until the next 5 years and evaluated by the metrics for binary classification.

To evaluate the contribution of the interaction effects to model performance, we estimated the effect sizes of interaction terms such as PRSage by logistic regression:

$$begin{array}{l}P({rm{RLS}}=1|{rm{PRS}},{rm{sex}},{rm{age}},{bf{PC}})\=displaystylefrac{1}{1+{e}^{-left({beta }_{0}+{beta }_{1}{rm{PRS}}+{beta }_{2}{rm{sex}}+{{beta }}_{3}{rm{age}}+{beta }_{4}{rm{PRS}}times {rm{sex}}+{{beta }}_{5}{ {rm{PRS}timesrm{age}}}+{{beta }}_{6}{{rm{sex}}timesrm{age}} +{{beta }}_{7}{{rm{PRS}}times {rm{sex}timesrm{age}}}+{boldsymbol{gamma }}cdot{bf{PC}}right)}},end{array}$$

where age is the dummy variable of age in bins of 20 years, PC indicates the first ten PCs from the MDS analysis in PLINK, is a vector of effect sizes of PCs and the PRS=jwjgj, where wj and gj are the per-allele effect size and dosage of the j-th SNP, respectively.

For the DNN and RF models, we used these logistic regression estimates as the baseline and then further estimated the interaction effect sizes indirectly by calculating the incremental gain in explained variance (Nagelkerkes pseudo-R2) from model0 to model1 as:

$${R}^{2}=left(1-left(Lleft(rm{model}_{0}right)/{it{L}}(rm{model}_{1})right)^{frac{2}{it{N}}}right)left(1-{it{L}}(rm{model}_{0})^{frac{2}{it{N}}}right)^{-1},$$

where L is the likelihood function for a logistic regression model with the first ten PCs included as covariates.

Binary classification models, GLMs and RF and DNN models were built, optimized and trained by H2O AutoML (version 3.36.0.2) in R (version 4.0.2)57. Time-to-event models were implemented with randomForestSRC (version 3.0.1) in R (version 4.0.2) and PyTorch58 (pycox version 0.2.1 and PyTorch version 1.6.0). Cross-validation-based Nagelkerkes pseudo-R2 was calculated in R version 4.0.2.

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

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Genome-wide meta-analyses of restless legs syndrome yield insights into genetic architecture, disease biology and ... - Nature.com

Biology

WT Biology Professor Wins Grant to Study Panhandle’s Pheasant Population – West Texas A&M University

Copy by Chip Chandler, 806-651-2124, cchandler@wtamu.edu

CANYON, Texas A West Texas A&M University faculty member recently earned an $860,000 grant to study the declining population of an economically important Panhandle bird.

Dr. Joshua Brown, assistant professor of biology in the Department of Life, Earth and Environmental Sciences in WTs Paul Engler College of Agriculture and Natural Sciences, is actively seeking area landowners to participate in a study of ring-necked pheasants in the High Plains.

The grant comes from Texas Parks and Wildlife Department, which has monitored the birds population since 1976 and have noticed a decline for decades. The department will use funds from the Federal Aid in Wildlife Restoration Act, which provides resources for state wildlife conservation agencies.

Browns study will examine the birds nesting habits, movements and population genetics to see if any new conservation strategies might be devised.

In doing so, hell utilize state-of-the-art technology.

Well trap birds, attach a 15-gram GPS tracker with a Teflon harness, take some blood, then let them go, Brown said. Well see where the birds are going with real-time information that will help us identify their potential nesting sites. Its a new use of GPS trackers. Traditionally, nest searching has been time intensive, requiring people in the field to manually search through brush for signs of a nest.

Once nests are located, Brown, two graduate students and his research technicians will do vegetation assessments and a modeling analysis to see what the characteristics of successful and unsuccessful nests are.

Eventually, well develop information that Texas Parks and Wildlife can disseminate to farmers and private landowners that they can incorporate on their property if theyre interested in conserving pheasants, Brown said.

Securing the grant is a significant accomplishment for Brown, said Dr. Jason Yarbrough, head of the Department of Life, Earth and Environmental Sciences.

Dr. Brown has proven to be an exceptional faculty member, Yarbrough said. He is a great colleague and a dedicated scientist who is off to a great start. We are proud to have him in the department.

Brown, who won his Colleges Young Faculty Award, said the grant was a perfect fit for him, both because he recently completed his first year as an assistant professor at WT and because the University is perfectly positioned to lead such research.

Pheasants, which arent native to the region, were first brought here because theyre fun to hunt and usually have self-sustaining populations, Brown said. In the 1980s and 90s, agricultural practices changed as far as harvesting and watering, and those changes resulted in habitats that arent as conducive to pheasants. The birds can certainly coexist with agriculture, but there are certain conditions for which that is more conducive.

Brown has already reached out to conservation group Pheasants Forever to help find landowners willing to let the research team do field work on their property. Others interested in taking part may contact Brown at 806-651-5217 or jbrown@wtamu.edu.

Leading such impactful studies as a Regional Research University is in line with the Universitys long-range plan, WT 125: From the Panhandle to the World.

That plan is fueled by the historicOne Westcomprehensive fundraising campaign, which reached its initial $125 million goal 18 months after publicly launching in September 2021. The campaigns new goal is to reach $175 million by 2025; currently, it has raised nearly $160 million.

About West Texas A&M University

WT is located in Canyon, Texas, on a 342-acre residential campus. Established in 1910, the University has been part of The Texas A&M University System since 1990. WT, a Hispanic Serving Institution since 2016, boasts an enrollment of about 10,000 and offers 59 undergraduate degree programs and more than 40 graduate degrees, including two doctoral degrees. The University is also home to the Panhandle-Plains Historical Museum, the largest history museum in the state and the home of one of the Southwests finest art collections. The Buffaloes are a member of the NCAA Division II Lone Star Conference and offers 14 mens and womens athletics programs.

WT

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WT Biology Professor Wins Grant to Study Panhandle's Pheasant Population - West Texas A&M University

Biology

Jessica Cottrell and Biology Student Mahika Ganguly Awarded STEM Undergraduate Research Award – Seton Hall University

Jessica Cottrell, Ph.D.

At the beginning of this year, Biology Chairperson Jessica Cottrell, Ph.D., and 2nd-year biology major in the joint B.S./M.D. program, Mahika Ganguly, were awarded a competitive STEM Undergraduate Research Award for their study, "The Effects of Vape Juice Additives on Chondrogenesis." Alternative forms of smoking continue to proliferate, but there is inadequate existing research detailing the potential harmful effects of these alternatives on cartilage cells. Cottrell and Mahika's research focuses on investigating how the flavorings found in vape juices, commonly used in e-smoking alternatives, influence chondrocyte (cells that make cartilage) proliferation and function. The study delves into the impact of popular vape juice flavors like cinnamon, strawberry, and mint on this biological process.

With this goal in mind, they are studying ATDC5 chondrocyte cells, a standard model for cartilage cellular sciences. To determine the effects that vape juice additives have on chondrogenesis, the two have examined the cellular response to increased concentrations of vape juice flavorings for up to 28 days. Because Cottrell and Mahika are studying the exclusive effects of the vape juice additives, not nicotine, they are examining how the growth of chondrocytes is impacted when nicotine is not present. When examining the growth of chondrocytes, Cottrell and Mahika measure the calcium deposition of these cells as a signifier for cellular function, that is, as evidence that the chondrocytes are properly functioning. So far, they have been able to observe that vape juice additives do have a negative impact on chondrogenesis, but they are trying to further determine if this reduced growth is a result of inflammation. Now that Cottrell and Mahika have observed the negative impacts, they will continue their study to identify at what concentration of vape juice additive cells result in the induction of an inflammatory response. This next step will be completed, by measuring the gene expression of these chondrocytes after vape juice exposure.

Mahika Ganguly, second-year biology student.

At the conclusion of this study, Cottrell and Mahika hope to bring attention to the harmful effects of vaping and electronic cigarettes, particularly on adolescents and young adults whose bodies should be growing. Additionally, the pair hope to continue their work into the summer and present their findings at the 2025 Petersheim Academic Exposition and the American Association of Immunologists. Ultimately, their goal is to present at the American Society of Bone and Mineral Research Conference.

Lab work is teamwork. Through the course of working together, Cottrell and Mahika have developed a mutual respect and appreciation for each other that extends beyond the lab. Cottrells ability to connect with students such as Mahika develops a deeper connection with biology. Cottrell enjoys working with undergraduates, especially because she gets the privilege of "allowing them to be inquisitive on their own and making them life-long learners."

Seton Hall has a robust Department of Biological Sciences with a wide range of faculty researching in microbiology, virology, immunology, and other areas. The Department offers both the Masters and Doctoral degrees, and Seton Hall is excited to announce a new 3+2 B.S./ M.S. Program that will enable students to earn a B.S. in Biological Sciences and an M.S. in Molecular Bioscience in just five years. Students interested in STEM research should contact Associate Dean Mitra Feizabadi and students interested in STEM graduate programs should contact Associate Dean Michael Dooney.

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Jessica Cottrell and Biology Student Mahika Ganguly Awarded STEM Undergraduate Research Award - Seton Hall University

Biology

Meet Our Pygmy Slow Loris Babies | Smithsonian’s National Zoo and Conservation Biology Institute – Smithsonian’s National Zoo and Conservation Biology…

How are Naga and Pabu adjusting to parenthood?

Pygmy slow loris mothers are the primary caregivers of their offspring. Naga is a first time mom. Initially, she seemed a bit confused but eventually settled into her new role. It took her some time to figure out how to carry the babies and decide where to put them down for the night. Over time, she became much more confident and is displaying all the natural behaviors we expect to see. Naga responds to the babies when they vocalize and will put them down and park them in a spot while she goes off to explore and eat.

Up until recently, she had been walking around with them riding on her stomach. Now, they are too large for her to carry. The babies have learned to move around on their own, so she is now free to leave and let them explore.

In the wild and in zoos, fathers occasionally interact with offspring, depending on their personality and past experience with babies. Pabu has proved to be an attentive and patient father. He has even carried the babies a few times. We often found him sitting with the babies. He seems very interested in them, but is not above stealing a snack from them.

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Biology

Student athlete Vinny DOnofrio 24 excelled in biology and chemistry at PLU – Pacific Lutheran University

How did soccer impact you?

I think it helped me grow as a person. I gained confidence in myself that I did not think I had at times, because people around me provided that backbone.

Tell me about your two majors.

I first started as just a biology major. I pursued pre-med classes. In my junior year, I took analytical chemistry, and the professor [Brian Naasz] said, You are pretty good at this. Why dont you take that plus year and stick around for next year and get the major too?

Who are your mentors?

I would say Dr. [Tina] Saxowsky, she sparked what I was most interested in. Dr. [Matt] Smith was my first biology professor. Dr. [Andrea] Munro helped me get the classes aligned to pursue the chemistry degree.

What did you learn as a biology TA and chemistry stockroom worker?

As a TA, I found myself learning new ideas from students that I might not have thought of, on the same question I had a couple of years ago. I love working with Maryls [Nesset], she puts me on dish duty, but that is what I choose to do. It humbles you. If I did not do this, people would not be able to do their lab experiments.

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Student athlete Vinny DOnofrio 24 excelled in biology and chemistry at PLU - Pacific Lutheran University

Biology

Obituary: Stan H. Braude, professor of practice in Arts & Sciences, 62 – The Source – Washington University in St. Louis

Stan Braude, a professor of practice in biology and in environmental studies in Arts & Sciences at Washington University in St. Louis, died at home Saturday, June 1, 2024, after a short illness. He was 62.

Braude earned his bachelors, masters and doctoral degrees in biology at the University of Michigan, spending summers at the universitys Biological Station in northern Michigan. He worked in Kenya for more than 20 years, becoming a world expert on naked mole-rat ecology, evolution and behavior in the wild. He also worked in Argentina, Djibouti, Ethiopia, Tanzania and Uganda and locally in Missouri.

In addition to his naked mole-rat research, Braude published articles and textbook materials on many different topics in ecology, evolution and conservation biology over the years, including elephant behavior, rhinoceros inbreeding and the evolution of dogs, as well as his research on dragonflies, tuco-tucos, giant pouched rats and cave salamanders. Braude was also interested in human biology publishing research on Barr Bodies, differential blood counts and the evolution of humor, for example and proposed several theories on medically relevant topics including testosterone levels, inflammatory bowel disease and the oncoprotective fever hypothesis.

Braude began his teaching career at Washington University in 1992 as a lecturer in University College, now known as the School of Continuing & Professional Studies, and started teaching full time in the Department of Biology in 1997.

He taught classes in human anatomy and physiology; advanced wilderness medicine; Missouris natural heritage (an Ampersand program class); and the woody plants of Missouri, among others. When teaching about the biology of dog breeds, Braude brought his oversized dogs to campus to participate in classes.

Braude received multiple national awards for teaching, including the 2004 College Biology Teacher of the Year award from the National Association of Biology Teachers and the 2011 Distinguished Teacher Award from the Animal Behavior Society. Locally, Braude was honored with the Emerson Excellence in Teaching Award in 2022 and the Arts & Sciences Distinguished Teaching Award in 2019.

Dr. Braude taught me to take ownership of how I act. He also showed me the importance of recognizing the impact of my actions in addition to my intentions, Alison Leslie, a 2017 alum, told a writer who profiled Braude and his effectiveness in the classroom in 2019. I truly believe that getting to know him through his courses has made me not only a better student but also a better person.

Stan was a consummate teacher, said Ram Dixit, a professor and chair of biology. He brought passion and creativity to the multitude of courses he taught in the biology department and in the University College program. His love of the outdoors and hands-on inquiry have had a lasting impact on many generations of students.

Braude was an active participant and mentor for research projects sponsored by the Living Earth Collaborative, the Institute for Public Health and Tyson Research Center, WashUs environmental field station. He was an animal trapper, fisherman, carpenter and gardener. He made his own camping gear and he foraged for wild edibles, a talent and skill that he taught to WashU undergraduates and younger scouts in the St. Louis area.Most recently, his knowledge of local foods led to collaborations with Bulrush restaurant and the universitys Buder Center for American Indian Studies.

For the last eight or nine years, weve been tapping the maple trees on campus and then boiling down all that sap into syrup for a pancake breakfast, Braude told the Humans of Tyson project in 2020. I make a fire outside and boil the sap over it. The last couple of years, I would start at around 6 in the morning and invite people from the Pathfinder class around 11, when we would have the first batch of syrup ready.

Certified as an EMT, wilderness medicine educator and arborist, Braude was the first curator of the Washington University arboretum, which attained Morton Arboretum Level II certification during his tenure. He initiated the love letters for trees event and continued the life of the oldest campus tree.

Braude had recently traveled to Cambridge, U.K., to trace the journey of Frederick Law Olmsted, the landscape architect who crafted the first plan for the WashU campus in 1895. With the support of a Newman Exploration Travel Award, he was seeking inspiration for the design of green spaces around the new Arts & Sciences building west of Olin Library.

Braude is survived by his wife, Nancy E. Berg, a professor of Hebrew language and literature in Arts & Sciences; children and extended family.

Services were held June 4. In lieu of flowers, the family requests donations to One Tree Planted, a local food pantry or a charity of your choice.

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Obituary: Stan H. Braude, professor of practice in Arts & Sciences, 62 - The Source - Washington University in St. Louis

Biology

Men and Women’s Different Biology Supports Their Different Roles – Answers In Genesis

The news cycle is consistently filled with articles about gender, sex, male, and female, in addition to a whole new dictionary of terms like nonbinary, two-spirit, cis-gender, pansexual, and so on. Our culture is obsessed with the idea of so-called sexual or gender identity. Rather than embracing Gods purposeful and unique design of male and female, they have exchanged the truth of God for a lie and worship the creature rather than the Creator (Romans 1:25). The alphabet mafia chooses to ignore Gods definitions and to redefine (or in many cases not define!) what it means to be male and female. They see the key to equality is for there to be NO differences between the sexes. In their view, we all just need to be the same.

We see examples of this in stores where clothing is no longer designated as mens OR womens and toys are no longer boys OR girls. We see it in sports where biological men are allowed to compete against biological women because the men identify as women. Courts are ruling that the male-only military draft may not be constitutional. A lawyer representing the National Coalition of Men said, Either they need to get rid of the draft registration or they need to require women to do the same thing that men do.1 At the 2023 American Anthropological Association (AAA) conference, a session about skeletal differences between males and females was canceled because it was considered transphobic. The AAA stated, There is no single biological standard by which all humans can be reliably sorted into a binary male/female sex classification.2 As a PhD geneticist, I can confidently say this is scientifically absurd, and as a Christian, I can say its biblically wrong as well.

God created males and females equalbut different. Thats not to say we dont have some sameness. We both bear the image of God (Genesis 1:2627). We both are sinners in need of salvation (Romans 3:23), and when we receive Christ as our Savior, we are one in Jesus (Galatians 3:28). But we are also different!

Women and men are both made in the image of God, but we have unique character qualities that cause us to bear that image differently. Elisabeth Elliot eloquently said, These two people [Adam and Eve] together represent the image of Godone of them in a special way the initiator, the other the responder. Neither the one nor the other was adequate alone to bear the divine image.3

Women tend to be caring and nurturing. God displays this characteristic vividly in Matthew 23:37, where Jesus speaking of the Israelites says, How often would I have gathered your children together as a hen gathers her brood under her wings. Men tend to be protectors and fight to protect those in their care. God displays this characteristic in Isaiah 42:13 where Isaiah says, The Lord goes out like a mighty man, like a man of war he stirs up his zeal; . . . he shows himself mighty against his foes. Women and men bear Gods image differently and that is part of Gods good design. We are equal but different. Im not saying that certain character qualities of God are exclusive to one sex or the other, but we tend to see certain characteristics more often or more clearly in one sex than the other, and that is good!

Men and women also have different functions and roles especially within marriage and the church. God created Eve as a helper to Adam (Genesis 2:18), and wives are to submit to their husbands (Ephesians 5:22). This doesnt imply an inferior/superior relationship within marriage; rather, it reflects different roles. We see this reflected in the Trinity as Jesus submits to the Father yet is equal to the Father. Husbands are to love their wives as their own bodies and as Christ loved the church by dying for her (Ephesians 5:2528). These different roles are an earthly reflection of the heavenly reality of the relationship between Christ and the church (Ephesians 5:32). Again, men and women are equal but different, and that is good!

Men and women are also biologically unique, and sometimes, we can even see directly how that biological design is related to our different character qualities and functions/roles. Gods design is truly purposeful! In this article, well explore some of the genetic and cellular differences between men and women.

Contrary to what the AAA said, there IS a single biological standard by which all humans can be reliably sorted into a binary male/female sex classification. Its called our sex chromosomes. Females have two X chromosomes, and males have one X and one Y chromosome. I have an easy saying to help people remember this: No Y, no guy! The Y chromosome has the sex-determining region Y gene (SRY for short) that inhibits female anatomical growth and induces the formation of male anatomy during embryo development. Some will argue there are sex chromosome abnormalities that make sex determination at birth or even puberty challenging. While these abnormalities are real in our fallen world (and these parents and children need compassion and support), it is never right to argue for normal from the abnormal.

Many of the genes on the Y chromosome (like SRY) are unique and dont have any match on the X chromosome. But there are some genes for basic cellular functions that exist on both the X and Y. Genes for basic cellular functions usually do not differ much within the human population because these are functions that all human cells must perform for people to live. However, scientists have discovered a gene, named RPS4, that has different versions on the X and Y chromosomes.4 This gene has the instructions for a ribosomal protein, and ribosomes assemble proteins in our cells. This means that male and female ribosomes are different. This blew my mind! The biological classification of mammals, which includes humans, dont really differ much in their ribosome makeup, yet God has seen fit to design male and female humans with different ribosomes. Why? I have no idea! Im excited to see more research that determines why this difference is important.

Although females have two X chromosomes, one of them is inactivated. Males only have one X chromosome and females in essence only have one active X chromosomeor so we thought. It turns out that 1523% of the genes on the so-called inactive X may still be active in that proteins are made from the genes.5 Many of those genes are thought to be related to the immune system, and as a result, women may have a more robust immune system. Women have higher circulating numbers of white blood cells and nearly every immune system response in females is higher.6 This relates well to a womans function/role in caring for children who often harbor a lot of germs! Also, women tend to have the character quality of being social and being in groups of people more often than men.b The gene activity on the inactive X may offer a protective mechanism against exposure to harmful bacteria and viruses often found in these social interactions. It also may mean that man flu is a real thing!

A 2017 gene activity study looked at 18,000 genes in 45 tissues to see if there were differences in activity between males and females.7 The researchers expected only a few hundred of these genes would show a difference. However, they found a whopping 6,500 genes (1/3 of those studied) have different activity levels!8 Some genes are active in men or women only, while some are much more active in one sex or the other. Much of the difference in activity levels is thought to relate to sex hormone differences. Testosterone in males and estrogen/progesterone in females likely causes genes to be read differently, resulting in different outcomes. One journalist in discussing these differences said, True equality is about respecting difference, not trying to erase it . . . . To be equal, men and women dont have to be the same. Which is just as well, because theyre not.9 Equality of the sexes should not, does not, and cannot mean sameness on a biological (or biblical) level. Thinking otherwise can have dangerous repercussions.

Differences in male/female genetics and their outcomes play a significant role in disease development, diagnosis, and treatment. For example, in males, fatty deposits in coronary arteries tend to be at specific locations, whereas in females, the deposits tend to line the artery more evenly, which makes heart disease harder to detect in females.10 Often, women are not included in clinical trials for the study and treatment of disease. This may explain why drugs that are effective at treating disease in men sometimes do not work in women. Its very likely that men and women metabolize drugs differently (because of sex chromosome and sex hormone differences), and what is an effective treatment in one sex may not be in the other.

Dr. Paula Johnson, founder and former executive director of the Connors Center for Womens Health and Gender Biology, stated, Today, we know that every cell has a sex. . . . And what it means is that men and women are different down to the cellular and molecular level. It means that were different across all of our organs, from our brains to our hearts, our lungs, our joints.11 Yes and amen! In part 1, weve learned some of many, many genetic and cellular differences between males and females. In part 2, well delve into the anatomical and physiological differences to understand more about how Gods unique biological designs of men and women relate to their character qualities and functions/roles. It truly is purposeful design!

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Men and Women's Different Biology Supports Their Different Roles - Answers In Genesis