Dark continuous noise from mutant G90D-rhodopsin predominantly underlies congenital stationary night blindness.

Congenital stationary night blindness (CSNB) is an inherited retinal disease that causes a profound loss of rod sensitivity without severe retinal degeneration. One well-studied rhodopsin point mutant, G90D-Rho, is thought to cause CSNB because of its constitutive activity in darkness causing rod desensitization. However, the nature of this constitutive activity and its precise molecular source have not been resolved for almost 30 y. In this study, we made a knock-in (KI) mouse line with a very low expression of G90D-Rho (equal in amount to ~0.1% of normal rhodopsin, WT-Rho, in WT rods), with the remaining WT-Rho replaced by REY-Rho, a mutant with a very low efficiency of activating transducin due to a charge reversal of the highly conserved ERY motif to REY. We observed two kinds of constitutive noise: one being spontaneous isomerization (R*) of G90D-Rho at a molecular rate (R* s-1) 175-fold higher than WT-Rho and the other being G90D-Rho-generated dark continuous noise comprising low-amplitude unitary events occurring at a very high molecular rate equivalent in effect to ~40,000-fold of R* s-1 from WT-Rho. Neither noise type originated from G90D-Opsin because exogenous 11-cis-retinal had no effect. Extrapolating the above observations at low (0.1%) expression of G90D-Rho to normal disease exhibited by a KI mouse model with RhoG90D/WTand RhoG90D/G90D genotypes predicts the disease condition very well quantitatively. Overall, the continuous noise from G90D-Rho therefore predominates, constituting the major equivalent background light causing rod desensitization in CSNB.

Autism-specific PTEN p.Ile135Leu variant and an autism genetic background combine to dysregulate cortical neurogenesis.

Alterations in cortical neurogenesis are implicated in neurodevelopmental disorders including autism spectrum disorders (ASDs). The contribution of genetic backgrounds, in addition to ASD risk genes, on cortical neurogenesis remains understudied. Here, using isogenic induced pluripotent stem cell (iPSC)-derived neural progenitor cells (NPCs) and cortical organoid models, we report that a heterozygous PTEN c.403A>C (p.Ile135Leu) variant found in an ASD-affected individual with macrocephaly dysregulates cortical neurogenesis in an ASD-genetic-background-dependent fashion. Transcriptome analysis at both bulk and single-cell level revealed that the PTEN c.403A>C variant and ASD genetic background affected genes involved in neurogenesis, neural development, and synapse signaling. We also found that this PTEN p.Ile135Leu variant led to overproduction of NPC subtypes as well as neuronal subtypes including both deep and upper layer neurons in its ASD background, but not when introduced into a control genetic background. These findings provide experimental evidence that both the PTEN p.Ile135Leu variant and ASD genetic background contribute to cellular features consistent with ASD associated with macrocephaly.

Biases in ARG-Based Inference of Historical Population Size in Populations Experiencing Selection.

Inferring the demographic history of populations provides fundamental insights into species dynamics and is essential for developing a null model to accurately study selective processes. However, background selection and selective sweeps can produce genomic signatures at linked sites that mimic or mask signals associated with historical population size change. While the theoretical biases introduced by the linked effects of selection have been well established, it is unclear whether ancestral recombination graph (ARG)-based approaches to demographic inference in typical empirical analyses are susceptible to misinference due to these effects. To address this, we developed highly realistic forward simulations of human and Drosophila melanogaster populations, including empirically estimated variability of gene density, mutation rates, recombination rates, purifying, and positive selection, across different historical demographic scenarios, to broadly assess the impact of selection on demographic inference using a genealogy-based approach. Our results indicate that the linked effects of selection minimally impact demographic inference for human populations, although it could cause misinference in populations with similar genome architecture and population parameters experiencing more frequent recurrent sweeps. We found that accurate demographic inference of D. melanogaster populations by ARG-based methods is compromised by the presence of pervasive background selection alone, leading to spurious inferences of recent population expansion, which may be further worsened by recurrent sweeps, depending on the proportion and strength of beneficial mutations. Caution and additional testing with species-specific simulations are needed when inferring population history with non-human populations using ARG-based approaches to avoid misinference due to the linked effects of selection.

Bead-by-bead normalization of single antigen assays: A necessary step for accurate detection of weak anti-HLA antibodies.

Ascertaining the presence of weakly positive anti-HLA donor-specific antibodies (DSA) in organ transplantation with multiplex single antigen beads assays may be challenging despite their high sensitivity due to technical variability issues. Through extensive datasets of Next-Generation Sequencing HLA typings and single antigen analyses, we reassessed the mean fluorescence intensity (MFI) positivity threshold of the assay to enhance accuracy. By showing that some beads were more prone to false positivity than others, we propose a nuanced approach that accounts for nonspecific intrinsic reactivities at the HLA antigen level, that is, on a bead-by-bead basis, as it enhances assay precision and reliability. This is substantiated by a comprehensive statistical analysis of MFI values and the implementation of the determination of a "Quantile Adjusted Threshold 500" (QAT500) value for each bead. Applied to DSA detection during patients' follow-up, this approach discriminated better and earlier low-strength DSA that would later raise their MFI above the clinically relevant threshold of 3000. Moving from a subjective interpretation to a more objective and precise methodology allows for standardizing HLA antibody and DSA detection. The study emphasizes the need for further research with real clinical data to validate and refine this approach.

Modeling the evolution of recombination plasticity: A prospective review.

Meiotic recombination is one of the main sources of genetic variation, a fundamental factor in the evolutionary adaptation of sexual eukaryotes. Yet, the role of variation in recombination rate and other recombination features remains underexplored. In this review, we focus on the sensitivity of recombination rates to different extrinsic and intrinsic factors. We briefly present the empirical evidence for recombination plasticity in response to environmental perturbations and/or poor genetic background and discuss theoretical models developed to explain how such plasticity could have evolved and how it can affect important population characteristics. We highlight a gap between the evidence, which comes mostly from experiments with diploids, and theory, which typically assumes haploid selection. Finally, we formulate open questions whose solving would help to outline conditions favoring recombination plasticity. This will contribute to answering the long-standing question of why sexual recombination exists despite its costs, since plastic recombination may be evolutionary advantageous even in selection regimes rejecting any non-zero constant recombination.

Social and genetic associations with educational performance in a Scandinavian welfare state.

Recent research has suggested that across Western developed societies, the influence of genetics on educational outcomes is relatively constant. However, the degree to which family environment matters varies, such that countries with high levels of intergenerational mobility have weaker associations of family background. Research in this vein has relied on twin-based estimates, which involve variance decomposition, so direct assessment of the association of genes and environments is not possible. In the present study, we approach the question by directly measuring the impact of child genotype, parental genetic nurture, and parental realized education on educational achievement in primary and secondary school. We deploy data from a social democratic context (Norway) and contrast our findings with those derived from more liberal welfare state contexts. Results point to genetics only confounding the relationship between parent status and offspring achievement to a small degree. Genetic nurture associations are similar to those in other societies. We find no, or very small, gene-environment interactions and parent-child genotype interactions with respect to test scores. In sum, in a Scandinavian welfare state context, both genetic and environmental associations are of similar magnitude as in societies with less-robust efforts to mitigate the influence of family background.

Loss-of-function mutation survey revealed that genes with background-dependent fitness are rare and functionally related in yeast.

In natural populations, the same mutation can lead to different phenotypic outcomes due to the genetic variation that exists among individuals. Such genetic background effects are commonly observed, including in the context of many human diseases. However, systematic characterization of these effects at the species level is still lacking to date. Here, we sought to comprehensively survey background-dependent traits associated with gene loss-of-function (LoF) mutations in 39 natural isolates of Saccharomyces cerevisiae using a transposon saturation strategy. By analyzing the modeled fitness variability of a total of 4,469 genes, we found that 15% of them, when impacted by a LoF mutation, exhibited a significant gain- or loss-of-fitness phenotype in certain natural isolates compared with the reference strain S288C. Out of these 632 genes with predicted background-dependent fitness effects, around 2/3 impact multiple backgrounds with a gradient of predicted fitness change while 1/3 are specific to a single genetic background. Genes related to mitochondrial function are significantly overrepresented in the set of genes showing a continuous variation and display a potential functional rewiring with other genes involved in transcription and chromatin remodeling as well as in nuclear-cytoplasmic transport. Such rewiring effects are likely modulated by both the genetic background and the environment. While background-specific cases are rare and span diverse cellular processes, they can be functionally related at the individual level. All genes with background-dependent fitness effects tend to have an intermediate connectivity in the global genetic interaction network and have shown relaxed selection pressure at the population level, highlighting their potential evolutionary characteristics.

Background-suppressed tumor-targeted photoacoustic imaging using bacterial carriers.

Photoacoustic (PA) imaging offers promise for biomedical applications due to its ability to image deep within biological tissues while providing detailed molecular information; however, its detection sensitivity is limited by high background signals that arise from endogenous chromophores. Genetic reporter proteins with photoswitchable properties enable the removal of background signals through the subtraction of PA images for each light-absorbing form. Unfortunately, the application of photoswitchable chromoproteins for tumor-targeted imaging has been hampered by the lack of an effective targeted delivery scheme; that is, photoswitchable probes must be delivered in vivo with high targeting efficiency and specificity. To overcome this limitation, we have developed a tumor-targeting delivery system in which tumor-homing bacteria (Escherichia coli) are exploited as carriers to affect the point-specific delivery of genetically encoded photochromic probes to the tumor area. To improve the efficiency of the desired background suppression, we engineered a phytochrome-based reporter protein (mDrBphP-PCMm/F469W) that displays higher photoswitching contrast than those in the current state of the art. Photoacoustic computed tomography was applied to achieve good depth and resolution in the context of in vivo (mice) imaging. The present system effectively integrates a genetically encoded phytochrome-based reporter protein, PA imaging, and synthetic biology (GPS), to achieve essentially background-suppressed tumor-targeted PA monitoring in deep-seated tissues. The ability to image tumors at substantial depths may enable target-specific cancer diagnoses to be made with greater sensitivity, fidelity, and specificity.

Switching between External and Internal Attention in Hippocampal Networks.

Everyday experience requires processing external signals from the world around us and internal information retrieved from memory. To do both, the brain must fluctuate between states that are optimized for external versus internal attention. Here, we focus on the hippocampus as a region that may serve at the interface between these forms of attention and ask how it switches between prioritizing sensory signals from the external world versus internal signals related to memories and thoughts. Pharmacological, computational, and animal studies have identified input from the cholinergic basal forebrain as important for biasing the hippocampus toward processing external information, whereas complementary research suggests the dorsal attention network (DAN) may aid in allocating attentional resources toward accessing internal information. We therefore tested the hypothesis that the basal forebrain and DAN drive the hippocampus toward external and internal attention, respectively. We used data from 29 human participants (17 female) who completed two attention tasks during fMRI. One task (memory-guided) required proportionally more internal attention, and proportionally less external attention, than the other (explicitly instructed). We discovered that background functional connectivity between the basal forebrain and hippocampus was stronger during the explicitly instructed versus memory-guided task. In contrast, DAN-hippocampus background connectivity was stronger during the memory-guided versus explicitly instructed task. Finally, the strength of DAN-hippocampus background connectivity was correlated with performance on the memory-guided but not explicitly instructed task. Together, these results provide evidence that the basal forebrain and DAN may modulate the hippocampus to switch between external and internal attention.SIGNIFICANCE STATEMENT How does the brain balance the need to pay attention to internal thoughts and external sensations? We focused on the human hippocampus, a region that may serve at the interface between internal and external attention, and asked how its functional connectivity varies based on attentional states. The hippocampus was more strongly coupled with the cholinergic basal forebrain when attentional states were guided by the external world rather than retrieved memories. This pattern flipped for functional connectivity between the hippocampus and dorsal attention network, which was higher for attention tasks that were guided by memory rather than external cues. Together, these findings show that distinct networks in the brain may modulate the hippocampus to switch between external and internal attention.

Site-Specific Identification of Protein S-Acylation by IodoTMT0 Labeling and Immobilized Anti-TMT Antibody Resin Enrichment.

Protein S-acylation is a reversible post-translational modification (PTM). It is present on diverse proteins and has important roles in regulating protein function. Aminolysis with hydroxylamine is widely used in the global identification of the PTM. However, the identification is indirect. Distinct criteria have been used for identification, and the false discovery rate has not been addressed. Here, we report a site-specific method for S-acylation identification based on tagging of S-acylation sites with iodoTMT0. Efforts to improve the performance of the method and confidence of identification are discussed, highlighting the importance of reducing contaminant peptides and keeping the recovery rate consistent between aliquots with or without hydroxylamine treatment. With very stringent criteria, presumptive S-acylation sites of 269, 684, 695, and 780 were identified from HK2 cells, HK11 cells, mouse brain, and mouse liver samples, respectively. Among them, the newly identified protein S-acylation sites are equivalent to 34% of human and 24% of mouse S-acylation sites reported previously. In addition, false-positive rates for S-acylation identification and S-acylation abundances were estimated. Significant differences in S-acylation abundance were found from different samples (from 0.08% in HK2 cells to 0.76% in mouse brain), and the false-positive rates were significantly higher for samples with a low abundance of S-acylation.

Fine mapping of meiotic crossovers in Brassica oleracea reveals patterns and variations depending on direction and combination of crosses.

Meiotic recombination is crucial for assuring proper segregation of parental chromosomes and generation of novel allelic combinations. As this process is tightly regulated, identifying factors influencing rate, and distribution of meiotic crossovers (COs) is of major importance, notably for plant breeding programs. However, high-resolution recombination maps are sparse in most crops including the Brassica genus and knowledge about intraspecific variation and sex differences is lacking. Here, we report fine-scale resolution recombination landscapes for 10 female and 10 male crosses in Brassica oleracea, by analyzing progenies of five large four-way-cross populations from two reciprocally crossed F1s per population. Parents are highly diverse inbred lines representing major crops, including broccoli, cauliflower, cabbage, kohlrabi, and kale. We produced approximately 4.56T Illumina data from 1248 progenies and identified 15 353 CO across the 10 reciprocal crosses, 51.13% of which being mapped to <10 kb. We revealed fairly similar Mb-scale recombination landscapes among all cross combinations and between the sexes, and provided evidence that these landscapes are largely independent of sequence divergence. We evidenced strong influence of gene density and large structural variations on CO formation in B. oleracea. Moreover, we found extensive variations in CO number depending on the direction and combination of the initial parents crossed with, for the first time, a striking interdependency between these factors. These data improve our current knowledge on meiotic recombination and are important for Brassica breeders.

Harmonic field extension for QSM with reduced spatial coverage using physics-informed generative adversarial network.

Quantitative susceptibility mapping (QSM) is frequently employed in investigating brain iron related to brain development and diseases within deep gray matter (DGM). Nonetheless, the acquisition of whole-brain QSM data is time-intensive. An alternative approach, focusing the QSM specifically on areas of interest such as the DGM by reducing the field-of-view (FOV), can significantly decrease scan times. However, severe susceptibility value underestimations have been reported during QSM reconstruction with a limited FOV, largely attributable to artifacts from incorrect background field removal in the boundary region. This presents a considerable barrier to the clinical use of QSM with small spatial coverages using conventional methods alone. To mitigate the propagation of these errors, we proposed a harmonic field extension method based on a physics-informed generative adversarial network. Both quantitative and qualitative results demonstrate that our method outperforms conventional methods and delivers results comparable to those obtained with full FOV. Furthermore, we demonstrate the versatility of our method by applying it to data acquired prospectively with limited FOV and to data from patients with Parkinson's disease. The method has shown significant improvements in local field results, with QSM outcomes. In a clear illustration of its feasibility and effectiveness in real clinical environments, our proposed method addresses the prevalent issue of susceptibility underestimation in QSM with small spatial coverage.

Genetics and diet shape the relationship between islet function and whole body metabolism.

Despite the fact that genes and the environment are known to play a central role in islet function, our knowledge of how these parameters interact to modulate insulin secretory function remains relatively poor. Presently, we performed ex vivo glucose-stimulated insulin secretion and insulin content assays in islets of 213 mice from 13 inbred mouse strains on chow, Western diet (WD), and a high-fat, carbohydrate-free (KETO) diet. Strikingly, among these 13 strains, islets from the commonly used C57BL/6J mouse strain were the least glucose responsive. Using matched metabolic phenotyping data, we performed correlation analyses of isolated islet parameters and found a positive correlation between basal and glucose-stimulated insulin secretion, but no relationship between insulin secretion and insulin content. Using in vivo metabolic measures, we found that glucose tolerance determines the relationship between ex vivo islet insulin secretion and plasma insulin levels. Finally, we showed that islet glucose-stimulated insulin secretion decreased with KETO in almost all strains, concomitant with broader phenotypic changes, such as increased adiposity and glucose intolerance. This is an important finding as it should caution against the application of KETO diet for beta-cell health. Together these data offer key insights into the intersection of diet and genetic background on islet function and whole body glucose metabolism.NEW & NOTEWORTHY Thirteen strains of mice on chow, Western diet, and high-fat, carbohydrate-free (KETO), correlating whole body phenotypes to ex vivo pancreatic islet functional measurements, were used. The study finds a huge spectrum of functional islet responses and insulin phenotypes across all strains and diets, with the ubiquitous C57Bl/6J mouse exhibiting the lowest secretory response of all strains, highlighting the overall importance of considering genetic background when investigating islet function. Ex vivo basal and stimulated insulin secretion are correlated in the islet, and KETO imparts widescale downregulation of islet insulin secretion.

Differential patterns of reproductive and lifestyle risk factors for breast cancer according to birth cohorts among women in China, Japan and Korea.

BACKGROUND: The birth cohort effect has been suggested to influence the rate of breast cancer incidence and the trends of associated reproductive and lifestyle factors. We conducted a cohort study to determine whether a differential pattern of associations exists between certain factors and breast cancer risk based on birth cohorts. METHODS: This was a cohort study using pooled data from 12 cohort studies. We analysed associations between reproductive (menarche age, menopause age, parity and age at first delivery) and lifestyle (smoking and alcohol consumption) factors and breast cancer risk. We obtained hazard ratios (HRs) with 95% confidence intervals (CIs) using the Cox proportional hazard regression analysis on the 1920s, 1930s, 1940s and 1950s birth cohorts. RESULTS: Parity was found to lower the risk of breast cancer in the older but not in the younger birth cohort, whereas lifestyle factors showed associations with breast cancer risk only among the participants born in the 1950s. In the younger birth cohort group, the effect size was lower for parous women compared to the other cohort groups (HR [95% CI] 0.86 [0.66-1.13] compared to 0.60 [0.49-0.73], 0.46 [0.38-0.56] and 0.62 [0.51-0.77]). Meanwhile, a higher effect size was found for smoking (1.45 [1.14-1.84] compared to 1.25 [0.99-1.58], 1.06 [0.85-1.32] and 0.86 [0.69-1.08]) and alcohol consumption (1.22 [1.01-1.48] compared to 1.10 [0.90-1.33], 1.15 [0.96-1.38], and 1.07 [0.91-1.26]). CONCLUSION: We observed different associations of parity, smoking and alcohol consumption with breast cancer risk across various birth cohorts.

Hypoactivation of the central auditory system in listeners who are hypertolerant of background noise.

Listeners exhibit varying levels of tolerance for background noise during speech communication. It has been proposed that low tolerance of background noise may be the consequence of abnormally amplified gain in the central auditory system (CAS). Here, using a dataset of young adults with normal hearing thresholds, we asked whether central gain mechanisms might also explain cases of hypertolerance of background noise, as well as cases of reduced, but not abnormal, tolerance. We used the auditory brainstem response to derive a measure of CAS gain (wave V/wave I ratio) to compare listeners' background noise tolerance while listening to speech, grouping them into three categories: hyper, high, and medium tolerance. We found that hypertolerant listeners had reduced CAS gain compared to those with high tolerance. This effect was driven by wave V not wave I. In addition, the medium tolerant listeners trended toward having reduced wave I and reduced wave V amplitudes and generally higher levels of exposure to loud sound, suggestive of the early stages of noise-compromised peripheral function without an apparent compensatory increase in central gain. Our results provide physiological evidence that 1) reduced CAS gain may account for hypertolerance of background noise but that 2) increased CAS gain is not a prerequisite for medium tolerance of background noise.NEW & NOTEWORTHY Our findings strengthen the proposed mechanistic connection between background noise tolerance and auditory physiology by suggesting a link between hypertolerance and reduced central auditory gain, measured by the auditory brainstem response.

Sunitinib-mediated inhibition of STAT3 in skeletal muscle and spinal cord does not affect the disease in a mouse model of ALS.

Variability in disease onset and progression is a hallmark of amyotrophic lateral sclerosis (ALS), both in sporadic and genetic forms. Recently, we found that SOD1-G93A transgenic mice expressing the same amount of mutant SOD1 but with different genetic backgrounds, C57BL/6JOlaHsd and 129S2/SvHsd, show slow and rapid muscle wasting and disease progression, respectively. Here, we investigated the different molecular mechanisms underlying muscle atrophy. Although both strains showed similar denervation-induced degradation of muscle proteins, only the rapidly progressing mice exhibited early and sustained STAT3 activation that preceded atrophy in gastrocnemius muscle. We therefore investigated the therapeutic potential of sunitinib, a tyrosine kinase inhibitor known to inhibit STAT3 and prevent cancer-induced muscle wasting. Although sunitinib treatment reduced STAT3 activation in the gastrocnemius muscle and lumbar spinal cord, it did not preserve spinal motor neurons, improve neuromuscular impairment, muscle atrophy and disease progression in the rapidly progressing SOD1-G93A mice. Thus, the effect of sunitinib is not equally positive in different diseases associated with muscle wasting. Moreover, given the complex role of STAT3 in the peripheral and central compartments of the neuromuscular system, the present study suggests that its broad inhibition may lead to opposing effects, ultimately preventing a potential positive therapeutic action in ALS.

Evolutionary "Crowdsourcing": Alignment of Fitness Landscapes Allows for Cross-species Adaptation of a Horizontally Transferred Gene.

Genes that undergo horizontal gene transfer (HGT) evolve in different genomic backgrounds. Despite the ubiquity of cross-species HGT, the effects of switching hosts on gene evolution remains understudied. Here, we present a framework to examine the evolutionary consequences of host-switching and apply this framework to an antibiotic resistance gene commonly found on conjugative plasmids. Specifically, we determined the adaptive landscape of this gene for a small set of mutationally connected genotypes in 3 enteric species. We uncovered that the landscape topographies were largely aligned with minimal host-dependent mutational effects. By simulating gene evolution over the experimentally gauged landscapes, we found that the adaptive evolution of the mobile gene in one species translated to adaptation in another. By simulating gene evolution over artificial landscapes, we found that sufficient alignment between landscapes ensures such "adaptive equivalency" across species. Thus, given adequate landscape alignment within a bacterial community, vehicles of HGT such as plasmids may enable a distributed form of genetic evolution across community members, where species can "crowdsource" adaptation.

Developing an Evolutionary Baseline Model for Humans: Jointly Inferring Purifying Selection with Population History.

Building evolutionarily appropriate baseline models for natural populations is not only important for answering fundamental questions in population genetics-including quantifying the relative contributions of adaptive versus nonadaptive processes-but also essential for identifying candidate loci experiencing relatively rare and episodic forms of selection (e.g., positive or balancing selection). Here, a baseline model was developed for a human population of West African ancestry, the Yoruba, comprising processes constantly operating on the genome (i.e., purifying and background selection, population size changes, recombination rate heterogeneity, and gene conversion). Specifically, to perform joint inference of selective effects with demography, an approximate Bayesian approach was employed that utilizes the decay of background selection effects around functional elements, taking into account genomic architecture. This approach inferred a recent 6-fold population growth together with a distribution of fitness effects that is skewed towards effectively neutral mutations. Importantly, these results further suggest that, although strong and/or frequent recurrent positive selection is inconsistent with observed data, weak to moderate positive selection is consistent but unidentifiable if rare.

Evolutionary Insights from a Large-Scale Survey of Population-Genomic Variation.

The field of genomics has ushered in new methods for studying molecular-genetic variation in natural populations. However, most population-genomic studies still rely on small sample sizes (typically, <100 individuals) from single time points, leaving considerable uncertainties with respect to the behavior of relatively young (and rare) alleles and, owing to the large sampling variance of measures of variation, to the specific gene targets of unusually strong selection. Genomic sequences of ∼1,700 haplotypes distributed over a 10-year period from a natural population of the microcrustacean Daphnia pulex reveal evolutionary-genomic features at a refined scale, including previously hidden information on the behavior of rare alleles predicted by recent theory. Background selection, resulting from the recurrent introduction of deleterious alleles, appears to strongly influence the dynamics of neutral alleles, inducing indirect negative selection on rare variants and positive selection on common variants. Temporally fluctuating selection increases the persistence of nonsynonymous alleles with intermediate frequencies, while reducing standing levels of variation at linked silent sites. Combined with the results from an equally large metapopulation survey of the study species, classes of genes that are under strong positive selection can now be confidently identified in this key model organism. Most notable among rapidly evolving Daphnia genes are those associated with ribosomes, mitochondrial functions, sensory systems, and lifespan determination.

Bonsai: An efficient method for inferring large human pedigrees from genotype data.

Pedigree inference from genotype data is a challenging problem, particularly when pedigrees are sparsely sampled and individuals may be distantly related to their closest genotyped relatives. We present a method that infers small pedigrees of close relatives and then assembles them into larger pedigrees. To assemble large pedigrees, we introduce several formulas and tools including a likelihood for the degree separating two small pedigrees, a generalization of the fast DRUID point estimate of the degree separating two pedigrees, a method for detecting individuals who share background identity-by-descent (IBD) that does not reflect recent common ancestry, and a method for identifying the ancestral branches through which distant relatives are connected. Our method also takes several approaches that help to improve the accuracy and efficiency of pedigree inference. In particular, we incorporate age information directly into the likelihood rather than using ages only for consistency checks and we employ a heuristic branch-and-bound-like approach to more efficiently explore the space of possible pedigrees. Together, these approaches make it possible to construct large pedigrees that are challenging or intractable for current inference methods.