The rapidly evolving X-linked MIR-506 family fine-tunes spermatogenesis to enhance sperm competition.

Despite rapid evolution across eutherian mammals, the X-linked MIR-506 family miRNAs are located in a region flanked by two highly conserved protein-coding genes (SLITRK2 and FMR1) on the X chromosome. Intriguingly, these miRNAs are predominantly expressed in the testis, suggesting a potential role in spermatogenesis and male fertility. Here, we report that the X-linked MIR-506 family miRNAs were derived from the MER91C DNA transposons. Selective inactivation of individual miRNAs or clusters caused no discernible defects, but simultaneous ablation of five clusters containing 19 members of the MIR-506 family led to reduced male fertility in mice. Despite normal sperm counts, motility, and morphology, the KO sperm were less competitive than wild-type sperm when subjected to a polyandrous mating scheme. Transcriptomic and bioinformatic analyses revealed that these X-linked MIR-506 family miRNAs, in addition to targeting a set of conserved genes, have more targets that are critical for spermatogenesis and embryonic development during evolution. Our data suggest that the MIR-506 family miRNAs function to enhance sperm competitiveness and reproductive fitness of the male by finetuning gene expression during spermatogenesis.

A common cis-regulatory variant impacts normal-range and disease-associated human facial shape through regulation of PKDCC during chondrogenesis.

Genome-wide association studies (GWAS) identified thousands of genetic variants linked to phenotypic traits and disease risk. However, mechanistic understanding of how GWAS variants influence complex morphological traits and can, in certain cases, simultaneously confer normal-range phenotypic variation and disease predisposition, is still largely lacking. Here, we focus on rs6740960, a single nucleotide polymorphism (SNP) at the 2p21 locus, which in GWAS studies has been associated both with normal-range variation in jaw shape and with an increased risk of non-syndromic orofacial clefting. Using in vitro derived embryonic cell types relevant for human facial morphogenesis, we show that this SNP resides in an enhancer that regulates chondrocytic expression of PKDCC - a gene encoding a tyrosine kinase involved in chondrogenesis and skeletal development. In agreement, we demonstrate that the rs6740960 SNP is sufficient to confer chondrocyte-specific differences in PKDCC expression. By deploying dense landmark morphometric analysis of skull elements in mice, we show that changes in Pkdcc dosage are associated with quantitative changes in the maxilla, mandible, and palatine bone shape that are concordant with the facial phenotypes and disease predisposition seen in humans. We further demonstrate that the frequency of the rs6740960 variant strongly deviated among different human populations, and that the activity of its cognate enhancer diverged in hominids. Our study provides a mechanistic explanation of how a common SNP can mediate normal-range and disease-associated morphological variation, with implications for the evolution of human facial features.

The Rapidly Evolving X-linked miR-506 Family Finetunes Spermatogenesis to Enhance Sperm Competition.

Despite rapid evolution across eutherian mammals, the X-linked miR-506 family miRNAs are located in a region flanked by two highly conserved protein-coding genes (Slitrk2 and Fmr1) on the X chromosome. Intriguingly, these miRNAs are predominantly expressed in the testis, suggesting a potential role in spermatogenesis and male fertility. Here, we report that the X-linked miR-506 family miRNAs were derived from the MER91C DNA transposons. Selective inactivation of individual miRNAs or clusters caused no discernable defects, but simultaneous ablation of five clusters containing nineteen members of the miR-506 family led to reduced male fertility in mice. Despite normal sperm counts, motility and morphology, the KO sperm were less competitive than wild-type sperm when subjected to a polyandrous mating scheme. Transcriptomic and bioinformatic analyses revealed that these X-linked miR-506 family miRNAs, in addition to targeting a set of conserved genes, have more targets that are critical for spermatogenesis and embryonic development during evolution. Our data suggest that the miR-506 family miRNAs function to enhance sperm competitiveness and reproductive fitness of the male by finetuning gene expression during spermatogenesis.

A genome-wide genetic screen uncovers determinants of human pigmentation.

Skin color, one of the most diverse human traits, is determined by the quantity, type, and distribution of melanin. In this study, we leveraged the light-scattering properties of melanin to conduct a genome-wide screen for regulators of melanogenesis. We identified 169 functionally diverse genes that converge on melanosome biogenesis, endosomal transport, and gene regulation, of which 135 represented previously unknown associations with pigmentation. In agreement with their melanin-promoting function, the majority of screen hits were up-regulated in melanocytes from darkly pigmented individuals. We further unraveled functions of KLF6 as a transcription factor that regulates melanosome maturation and pigmentation in vivo, and of the endosomal trafficking protein COMMD3 in modulating melanosomal pH. Our study reveals a plethora of melanin-promoting genes, with broad implications for human variation, cell biology, and medicine.

Genome scans of facial features in East Africans and cross-population comparisons reveal novel associations.

Facial morphology is highly variable, both within and among human populations, and a sizable portion of this variation is attributable to genetics. Previous genome scans have revealed more than 100 genetic loci associated with different aspects of normal-range facial variation. Most of these loci have been detected in Europeans, with few studies focusing on other ancestral groups. Consequently, the degree to which facial traits share a common genetic basis across diverse sets of humans remains largely unknown. We therefore investigated the genetic basis of facial morphology in an East African cohort. We applied an open-ended data-driven phenotyping approach to a sample of 2,595 3D facial images collected on Tanzanian children. This approach segments the face into hierarchically arranged, multivariate features that capture the shape variation after adjusting for age, sex, height, weight, facial size and population stratification. Genome scans of these multivariate shape phenotypes revealed significant (p < 2.5 × 10-8) signals at 20 loci, which were enriched for active chromatin elements in human cranial neural crest cells and embryonic craniofacial tissue, consistent with an early developmental origin of the facial variation. Two of these associations were in highly conserved regions showing craniofacial-specific enhancer activity during embryological development (5q31.1 and 12q21.31). Six of the 20 loci surpassed a stricter threshold accounting for multiple phenotypes with study-wide significance (p < 6.25 × 10-10). Cross-population comparisons indicated 10 association signals were shared with Europeans (seven sharing the same associated SNP), and facilitated fine-mapping of causal variants at previously reported loci. Taken together, these results may point to both shared and population-specific components to the genetic architecture of facial variation.

Insights into the genetic architecture of the human face.

The human face is complex and multipartite, and characterization of its genetic architecture remains challenging. Using a multivariate genome-wide association study meta-analysis of 8,246 European individuals, we identified 203 genome-wide-significant signals (120 also study-wide significant) associated with normal-range facial variation. Follow-up analyses indicate that the regions surrounding these signals are enriched for enhancer activity in cranial neural crest cells and craniofacial tissues, several regions harbor multiple signals with associations to different facial phenotypes, and there is evidence for potential coordinated actions of variants. In summary, our analyses provide insights into the understanding of how complex morphological traits are shaped by both individual and coordinated genetic actions.

FaceBase 3: analytical tools and FAIR resources for craniofacial and dental research.

The FaceBase Consortium was established by the National Institute of Dental and Craniofacial Research in 2009 as a 'big data' resource for the craniofacial research community. Over the past decade, researchers have deposited hundreds of annotated and curated datasets on both normal and disordered craniofacial development in FaceBase, all freely available to the research community on the FaceBase Hub website. The Hub has developed numerous visualization and analysis tools designed to promote integration of multidisciplinary data while remaining dedicated to the FAIR principles of data management (findability, accessibility, interoperability and reusability) and providing a faceted search infrastructure for locating desired data efficiently. Summaries of the datasets generated by the FaceBase projects from 2014 to 2019 are provided here. FaceBase 3 now welcomes contributions of data on craniofacial and dental development in humans, model organisms and cell lines. Collectively, the FaceBase Consortium, along with other NIH-supported data resources, provide a continuously growing, dynamic and current resource for the scientific community while improving data reproducibility and fulfilling data sharing requirements.

Deep experimental profiling of microRNA diversity, deployment, and evolution across the Drosophila genus.

To assess miRNA evolution across the Drosophila genus, we analyzed several billion small RNA reads across 12 fruit fly species. These data permit comprehensive curation of species- and clade-specific variation in miRNA identity, abundance, and processing. Among well-conserved miRNAs, we observed unexpected cases of clade-specific variation in 5' end precision, occasional antisense loci, and putatively noncanonical loci. We also used strict criteria to identify a large set (649) of novel, evolutionarily restricted miRNAs. Within the bulk collection of species-restricted miRNAs, two notable subpopulations are splicing-derived mirtrons and testes-restricted, recently evolved, clustered (TRC) canonical miRNAs. We quantified miRNA birth and death using our annotation and a phylogenetic model for estimating rates of miRNA turnover. We observed striking differences in birth and death rates across miRNA classes defined by biogenesis pathway, genomic clustering, and tissue restriction, and even identified flux heterogeneity among Drosophila clades. In particular, distinct molecular rationales underlie the distinct evolutionary behavior of different miRNA classes. Mirtrons are associated with high rates of 3' untemplated addition, a mechanism that impedes their biogenesis, whereas TRC miRNAs appear to evolve under positive selection. Altogether, these data reveal miRNA diversity among Drosophila species and principles underlying their emergence and evolution.

New genes often acquire male-specific functions but rarely become essential in Drosophila.

Relatively little is known about the in vivo functions of newly emerging genes, especially in metazoans. Although prior RNAi studies reported prevalent lethality among young gene knockdowns, our phylogenomic analyses reveal that young Drosophila genes are frequently restricted to the nonessential male reproductive system. We performed large-scale CRISPR/Cas9 mutagenesis of "conserved, essential" and "young, RNAi-lethal" genes and broadly confirmed the lethality of the former but the viability of the latter. Nevertheless, certain young gene mutants exhibit defective spermatogenesis and/or male sterility. Moreover, we detected widespread signatures of positive selection on young male-biased genes. Thus, young genes have a preferential impact on male reproductive system function.

Analysis of Nearly One Thousand Mammalian Mirtrons Reveals Novel Features of Dicer Substrates.

Mirtrons are microRNA (miRNA) substrates that utilize the splicing machinery to bypass the necessity of Drosha cleavage for their biogenesis. Expanding our recent efforts for mammalian mirtron annotation, we use meta-analysis of aggregate datasets to identify ~500 novel mouse and human introns that confidently generate diced small RNA duplexes. These comprise nearly 1000 total loci distributed in four splicing-mediated biogenesis subclasses, with 5'-tailed mirtrons as, by far, the dominant subtype. Thus, mirtrons surprisingly comprise a substantial fraction of endogenous Dicer substrates in mammalian genomes. Although mirtron-derived small RNAs exhibit overall expression correlation with their host mRNAs, we observe a subset with substantial differences that suggest regulated processing or accumulation. We identify characteristic sequence, length, and structural features of mirtron loci that distinguish them from bulk introns, and find that mirtrons preferentially emerge from genes with larger numbers of introns. While mirtrons generate miRNA-class regulatory RNAs, we also find that mirtrons exhibit many features that distinguish them from canonical miRNAs. We observe that conventional mirtron hairpins are substantially longer than Drosha-generated pre-miRNAs, indicating that the characteristic length of canonical pre-miRNAs is not a general feature of Dicer substrate hairpins. In addition, mammalian mirtrons exhibit unique patterns of ordered 5' and 3' heterogeneity, which reveal hidden complexity in miRNA processing pathways. These include broad 3'-uridylation of mirtron hairpins, atypically heterogeneous 5' termini that may result from exonucleolytic processing, and occasionally robust decapitation of the 5' guanine (G) of mirtron-5p species defined by splicing. Altogether, this study reveals that this extensive class of non-canonical miRNA bears a multitude of characteristic properties, many of which raise general mechanistic questions regarding the processing of endogenous hairpin transcripts.

Global diversity lines - a five-continent reference panel of sequenced Drosophila melanogaster strains.

Reference collections of multiple Drosophila lines with accumulating collections of "omics" data have proven especially valuable for the study of population genetics and complex trait genetics. Here we present a description of a resource collection of 84 strains of Drosophila melanogaster whose genome sequences were obtained after 12 generations of full-sib inbreeding. The initial rationale for this resource was to foster development of a systems biology platform for modeling metabolic regulation by the use of natural polymorphisms as perturbations. As reference lines, they are amenable to repeated phenotypic measurements, and already a large collection of metabolic traits have been assayed. Another key feature of these strains is their widespread geographic origin, coming from Beijing, Ithaca, Netherlands, Tasmania, and Zimbabwe. After obtaining 12.5× coverage of paired-end Illumina sequence reads, SNP and indel calls were made with the GATK platform. Thorough quality control was enabled by deep sequencing one line to >100×, and single-nucleotide polymorphisms and indels were validated using ddRAD-sequencing as an orthogonal platform. In addition, a series of preliminary population genetic tests were performed with these single-nucleotide polymorphism data for assessment of data quality. We found 83 segregating inversions among the lines, and as expected these were especially abundant in the African sample. We anticipate that this will make a useful addition to the set of reference D. melanogaster strains, thanks to its geographic structuring and unusually high level of genetic diversity.

A deeply conserved, noncanonical miRNA hosted by ribosomal DNA.

Advances in small RNA sequencing technologies and comparative genomics have fueled comprehensive microRNA (miRNA) gene annotations in humans and model organisms. Although new miRNAs continue to be discovered in recent years, these have universally been lowly expressed, recently evolved, and of debatable endogenous activity, leading to the general assumption that virtually all biologically important miRNAs have been identified. Here, we analyzed small RNAs that emanate from the highly repetitive rDNA arrays of Drosophila. In addition to endo-siRNAs derived from sense and antisense strands of the pre-rRNA sequence, we unexpectedly identified a novel, deeply conserved, noncanonical miRNA. Although this miRNA is widely expressed, this miRNA was not identified by previous studies due to bioinformatics filters removing such repetitive sequences. Deep-sequencing data provide clear evidence for specific processing with precisely defined 5' and 3' ends. Furthermore, we demonstrate that the mature miRNA species is incorporated in the effector complexes and has detectable trans regulatory activity. Processing of this miRNA requires Dicer-1, whereas the Drosha-Pasha complex is dispensable. The miRNA hairpin sequence is located in the internal transcribed spacer 1 region of rDNA and is highly conserved among Dipteran species that were separated from their common ancestor ∼ 100 million years ago. Our results suggest that biologically active miRNA genes may remain unidentified even in well-studied organisms.

Diverse modes of evolutionary emergence and flux of conserved microRNA clusters.

Many animal miRNA loci reside in genomic clusters that generate multicistronic primary-miRNA transcripts. While clusters that contain copies of the same miRNA hairpin are clearly products of local duplications, the evolutionary provenance of clusters with disparate members is less clear. Recently, it was proposed that essentially all such clusters in Drosophila derived from de novo formation of miRNA-like hairpins within existing miRNA transcripts, and that the maintenance of multiple miRNAs in such clusters was due to evolutionary hitchhiking on a major cluster member. However, this model seems at odds with the fact that many such miRNA clusters are composed of well-conserved miRNAs. In an effort to trace the birth and expansion of miRNA clusters that are presently well-conserved across Drosophilids, we analyzed a broad swath of metazoan species, with particular emphasis on arthropod evolution. Beyond duplication and de novo birth, we highlight a diversity of modes that contribute to miRNA evolution, including neofunctionalization of miRNA copies, fissioning of locally duplicated miRNA clusters, miRNA deletion, and miRNA cluster expansion via the acquisition and/or neofunctionalization of miRNA copies from elsewhere in the genome. In particular, we suggest that miRNA clustering by acquisition represents an expedient strategy to bring cohorts of target genes under coordinate control by miRNAs that had already been individually selected for regulatory impact on the transcriptome.

Diversity of miRNAs, siRNAs, and piRNAs across 25 Drosophila cell lines.

We expanded the knowledge base for Drosophila cell line transcriptomes by deeply sequencing their small RNAs. In total, we analyzed more than 1 billion raw reads from 53 libraries across 25 cell lines. We verify reproducibility of biological replicate data sets, determine common and distinct aspects of miRNA expression across cell lines, and infer the global impact of miRNAs on cell line transcriptomes. We next characterize their commonalities and differences in endo-siRNA populations. Interestingly, most cell lines exhibit enhanced TE-siRNA production relative to tissues, suggesting this as a common aspect of cell immortalization. We also broadly extend annotations of cis-NAT-siRNA loci, identifying ones with common expression across diverse cells and tissues, as well as cell-restricted loci. Finally, we characterize small RNAs in a set of ovary-derived cell lines, including somatic cells (OSS and OSC) and a mixed germline/somatic cell population (fGS/OSS) that exhibits ping-pong piRNA signatures. Collectively, the ovary data reveal new genic piRNA loci, including unusual configurations of piRNA-generating regions. Together with the companion analysis of mRNAs described in a previous study, these small RNA data provide comprehensive information on the transcriptional landscape of diverse Drosophila cell lines. These data should encourage broader usage of fly cell lines, beyond the few that are presently in common usage.

Adaptive evolution of testis-specific, recently evolved, clustered miRNAs in Drosophila.

The propensity of animal miRNAs to regulate targets bearing modest complementarity, most notably via pairing with miRNA positions ∼2-8 (the "seed"), is believed to drive major aspects of miRNA evolution. First, minimal targeting requirements have allowed most conserved miRNAs to acquire large target cohorts, thus imposing strong selection on miRNAs to maintain their seed sequences. Second, the modest pairing needed for repression suggests that evolutionarily nascent miRNAs may generally induce net detrimental, rather than beneficial, regulatory effects. Hence, levels and activities of newly emerged miRNAs are expected to be limited to preserve the status quo of gene expression. In this study, we unexpectedly show that Drosophila testes specifically express a substantial miRNA population that contravenes these tenets. We find that multiple genomic clusters of testis-restricted miRNAs harbor recently evolved miRNAs, whose experimentally verified orthologs exhibit divergent sequences, even within seed regions. Moreover, this class of miRNAs exhibits higher expression and greater phenotypic capacities in transgenic misexpression assays than do non-testis-restricted miRNAs of similar evolutionary age. These observations suggest that these testis-restricted miRNAs may be evolving adaptively, and several methods of evolutionary analysis provide strong support for this notion. Consistent with this, proof-of-principle tests show that orthologous miRNAs with divergent seeds can distinguish target sensors in a species-cognate manner. Finally, we observe that testis-restricted miRNA clusters exhibit extraordinary dynamics of miRNA gene flux in other Drosophila species. Altogether, our findings reveal a surprising tissue-directed influence of miRNA evolution, involving a distinct mode of miRNA function connected to adaptive gene regulation in the testis.

The impact of age, biogenesis, and genomic clustering on Drosophila microRNA evolution.

The molecular evolutionary signatures of miRNAs inform our understanding of their emergence, biogenesis, and function. The known signatures of miRNA evolution have derived mostly from the analysis of deeply conserved, canonical loci. In this study, we examine the impact of age, biogenesis pathway, and genomic arrangement on the evolutionary properties of Drosophila miRNAs. Crucial to the accuracy of our results was our curation of high-quality miRNA alignments, which included nearly 150 corrections to ortholog calls and nucleotide sequences of the global 12-way Drosophilid alignments currently available. Using these data, we studied primary sequence conservation, normalized free-energy values, and types of structure-preserving substitutions. We expand upon common miRNA evolutionary patterns that reflect fundamental features of miRNAs that are under functional selection. We observe that melanogaster-subgroup-specific miRNAs, although recently emerged and rapidly evolving, nonetheless exhibit evolutionary signatures that are similar to well-conserved miRNAs and distinct from other structured noncoding RNAs and bulk conserved non-miRNA hairpins. This provides evidence that even young miRNAs may be selected for regulatory activities. More strikingly, we observe that mirtrons and clustered miRNAs both exhibit distinct evolutionary properties relative to solo, well-conserved miRNAs, even after controlling for sequence depth. These studies highlight the previously unappreciated impact of biogenesis strategy and genomic location on the evolutionary dynamics of miRNAs, and affirm that miRNAs do not evolve as a unitary class.

Inference of natural selection from interspersed genomic elements based on polymorphism and divergence.

Complete genome sequences contain valuable information about natural selection, but this information is difficult to access for short, widely scattered noncoding elements such as transcription factor binding sites or small noncoding RNAs. Here, we introduce a new computational method, called Inference of Natural Selection from Interspersed Genomically coHerent elemenTs (INSIGHT), for measuring the influence of natural selection on such elements. INSIGHT uses a generative probabilistic model to contrast patterns of polymorphism and divergence in the elements of interest with those in flanking neutral sites, pooling weak information from many short elements in a manner that accounts for variation among loci in mutation rates and coalescent times. The method is able to disentangle the contributions of weak negative, strong negative, and positive selection based on their distinct effects on patterns of polymorphism and divergence. It obtains information about divergence from multiple outgroup genomes using a general statistical phylogenetic approach. The INSIGHT model is efficiently fitted to genome-wide data using an approximate expectation maximization algorithm. Using simulations, we show that the method can accurately estimate the parameters of interest even in complex demographic scenarios, and that it significantly improves on methods based on summary statistics describing polymorphism and divergence. To demonstrate the usefulness of INSIGHT, we apply it to several classes of human noncoding RNAs and to GATA2-binding sites in the human genome.

Genome-scale analysis of interaction dynamics reveals organization of biological networks.

Analyzing large-scale interaction networks has generated numerous insights in systems biology. However, such studies have primarily been focused on highly co-expressed, stable interactions. Most transient interactions that carry out equally important functions, especially in signal transduction pathways, are yet to be elucidated and are often wrongly discarded as false positives. Here, we revisit a previously described Smith-Waterman-like dynamic programming algorithm and use it to distinguish stable and transient interactions on a genomic scale in human and yeast. We find that in biological networks, transient interactions are key links topologically connecting tightly regulated functional modules formed by stable interactions and are essential to maintaining the integrity of cellular networks. We also perform a systematic analysis of interaction dynamics across different technologies and find that high-throughput yeast two-hybrid is the only available technology for detecting transient interactions on a large scale.

Distance-based clustering of CGH data.

MOTIVATION: We consider the problem of clustering a population of Comparative Genomic Hybridization (CGH) data samples. The goal is to develop a systematic way of placing patients with similar CGH imbalance profiles into the same cluster. Our expectation is that patients with the same cancer types will generally belong to the same cluster as their underlying CGH profiles will be similar. RESULTS: We focus on distance-based clustering strategies. We do this in two steps. (1) Distances of all pairs of CGH samples are computed. (2) CGH samples are clustered based on this distance. We develop three pairwise distance/similarity measures, namely raw, cosine and sim. Raw measure disregards correlation between contiguous genomic intervals. It compares the aberrations in each genomic interval separately. The remaining measures assume that consecutive genomic intervals may be correlated. Cosine maps pairs of CGH samples into vectors in a high-dimensional space and measures the angle between them. Sim measures the number of independent common aberrations. We test our distance/similarity measures on three well known clustering algorithms, bottom-up, top-down and k-means with and without centroid shrinking. Our results show that sim consistently performs better than the remaining measures. This indicates that the correlation of neighboring genomic intervals should be considered in the structural analysis of CGH datasets. The combination of sim with top-down clustering emerged as the best approach. AVAILABILITY: All software developed in this article and all the datasets are available from the authors upon request. CONTACT: juliu@cise.ufl.edu.