FineMAV: prioritizing candidate genetic variants driving local adaptations in human populations

Single-cell transcriptomics is revolutionizing the improvement of plant biotechnology research: recent advances and future opportunities

Single-cell approaches are a promising way to obtain high-resolution transcriptomics data and have the potential to revolutionize the study of plant growth and development. Recent years have seen the advent of unprecedented technological advances in the field of plant biology to study the transcriptional information of individual cells by single-cell RNA sequencing (scRNA-seq). This review focuses on the modern advancements of single-cell transcriptomics in plants over the past few years. In addition, it also offers a new insight of how these emerging methods will expedite advance research in plant biotechnology in the near future. Lastly, the various technological hurdles and inherent limitations of single-cell technology that need to be conquered to develop such outstanding possible knowledge gain is critically analyzed and discussed.

Population Genomic Analysis of Diploid-Autopolyploid Species

This chapter outlines an empirical analysis of genome-wide single-nucleotide polymorphism (SNP) variation and its underlying drivers among multiple natural populations within a diploid-autopolyploid species. The aim is to reconstruct the genetic structure among natural populations of varying ploidy and infer footprints of selection in these populations, framed around specific questions that are typically encountered when analyzing a mixed-ploidy data set,e.g., addressing the relevance of natural whole-genome duplication for speciation and adaptation. We briefly review the options for the analysis of polyploid population genomic data involving variant calling, population structure, demographic history inference, and selection scanning approaches. Further, we provide suggestions for methods and associated software, possible caveats, and examples of their application to mixed-ploidy and autopolyploid data sets.

Uncovering the extensive trade-off between adaptive evolution and disease susceptibility

Favored mutations in the human genome may make the carriers adapt to changing environments and lifestyles but also susceptible to specific diseases. The scale and details of the trade-off between adaptive evolution and disease susceptibility are unclear because most favored mutations in different populations remain unidentified. As no statistical test can discriminate favored mutations from nearby hitchhiking neutral ones, we report a deep-learning network (DeepFavored) to integrate multiple statistical tests and divide identifying favored mutations into two subtasks. We identify favored mutations in three human populations and analyzed the correlation between favored/hitchhiking mutations and genome-wide association study (GWAS) sites. Both favored and hitchhiking neutral mutations are enriched in GWAS sites with population-specific features, and the enrichment and population specificity are prominent in genes in specific Gene Ontology (GO) terms. These provide evidence for extensive and population-specific trade-offs between adaptive evolution and disease susceptibility. The unveiled scale helps understand and investigate differences and diseases of humans.

Prioritising positively selected variants in whole-genome sequencing data using FineMAV

Background

In population genomics, polymorphisms that are highly differentiated between geographically separated populations are often suggestive of Darwinian positive selection. Genomic scans have highlighted several such regions in African and non-African populations, but only a handful of these have functional data that clearly associates candidate variations driving the selection process. Fine-Mapping of Adaptive Variation (FineMAV) was developed to address this in a high-throughput manner using population based whole-genome sequences generated by the 1000 Genomes Project. It pinpoints positively selected genetic variants in sequencing data by prioritizing high frequency, population-specific and functional derived alleles.

Results

We developed a stand-alone software that implements the FineMAV statistic. To graphically visualise the FineMAV scores, it outputs the statistics as bigWig files, which is a common file format supported by many genome browsers. It is available as a command-line and graphical user interface. The software was tested by replicating the FineMAV scores obtained using 1000 Genomes Project African, European, East and South Asian populations and subsequently applied to whole-genome sequencing datasets from Singapore and China to highlight population specific variants that can be subsequently modelled. The software tool is publicly available at https://github.com/fadilla-wahyudi/finemav.

Conclusions

The software tool described here determines genome-wide FineMAV scores, using low or high-coverage whole-genome sequencing datasets, that can be used to prioritize a list of population specific, highly differentiated candidate variants for in vitro or in vivo functional screens. The tool displays these scores on the human genome browsers for easy visualisation, annotation and comparison between different genomic regions in worldwide human populations.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04506-9.

A Positively Selected MAGEE2 LoF Allele Is Associated with Sexual Dimorphism in Human Brain Size and Shows Similar Phenotypes in Magee2 Null Mice

A nonsense allele at rs1343879 in human MAGEE2 on chromosome X has previously been reported as a strong candidate for positive selection in East Asia. This premature stop codon causing ∼80% protein truncation is characterized by a striking geographical pattern of high population differentiation: common in Asia and the Americas (up to 84% in the 1000 Genomes Project East Asians) but rare elsewhere. Here, we generated a Magee2 mouse knockout mimicking the human loss-of-function mutation to study its functional consequences. The Magee2 null mice did not exhibit gross abnormalities apart from enlarged brain structures (13% increased total brain area, P = 0.0022) in hemizygous males. The area of the granular retrosplenial cortex responsible for memory, navigation, and spatial information processing was the most severely affected, exhibiting an enlargement of 34% (P = 3.4×10-6). The brain size in homozygous females showed the opposite trend of reduced brain size, although this did not reach statistical significance. With these insights, we performed human association analyses between brain size measurements and rs1343879 genotypes in 141 Chinese volunteers with brain MRI scans, replicating the sexual dimorphism seen in the knockout mouse model. The derived stop gain allele was significantly associated with a larger volume of gray matter in males (P = 0.00094), and smaller volumes of gray (P = 0.00021) and white (P = 0.0015) matter in females. It is unclear whether or not the observed neuroanatomical phenotypes affect behavior or cognition, but it might have been the driving force underlying the positive selection in humans.

De Novo Mutation and Rapid Protein (Co-)evolution during Meiotic Adaptation in Arabidopsis arenosa

A sudden shift in environment or cellular context necessitates rapid adaptation. A dramatic example is genome duplication, which leads to polyploidy. In such situations, the waiting time for new mutations might be prohibitive; theoretical and empirical studies suggest that rapid adaptation will largely rely on standing variation already present in source populations. Here, we investigate the evolution of meiosis proteins in Arabidopsis arenosa, some of which were previously implicated in adaptation to polyploidy, and in a diploid, habitat. A striking and unexplained feature of prior results was the large number of amino acid changes in multiple interacting proteins, especially in the relatively young tetraploid. Here, we investigate whether selection on meiosis genes is found in other lineages, how the polyploid may have accumulated so many differences, and whether derived variants were selected from standing variation. We use a range-wide sample of 145 resequenced genomes of diploid and tetraploid A. arenosa, with new genome assemblies. We confirmed signals of positive selection in the polyploid and diploid lineages they were previously reported in and find additional meiosis genes with evidence of selection. We show that the polyploid lineage stands out both qualitatively and quantitatively. Compared with diploids, meiosis proteins in the polyploid have more amino acid changes and a higher proportion affecting more strongly conserved sites. We find evidence that in tetraploids, positive selection may have commonly acted on de novo mutations. Several tests provide hints that coevolution, and in some cases, multinucleotide mutations, might contribute to rapid accumulation of changes in meiotic proteins.

Novelty and convergence in adaptation to whole genome duplication

Whole genome duplication (WGD) can promote adaptation but is disruptive to conserved processes, especially meiosis. Studies in Arabidopsis arenosa revealed a coordinated evolutionary response to WGD involving interacting proteins controlling meiotic crossovers, which are minimised in an autotetraploid (within-species polyploid) to avoid mis-segregation. Here we test whether this surprising flexibility of a conserved essential process, meiosis, is recapitulated in an independent WGD system, Cardamine amara, 17 million years diverged from A. arenosa. We assess meiotic stability and perform population-based scans for positive selection, contrasting the genomic response to WGD in C. amara with that of A. arenosa. We found in C. amara the strongest selection signals at genes with predicted functions thought important to adaptation to WGD: meiosis, chromosome remodelling, cell cycle, and ion transport. However, genomic responses to WGD in the two species differ: minimal ortholog-level convergence emerged, with none of the meiosis genes found in A. arenosa exhibiting strong signal in C. amara. This is consistent with our observations of lower meiotic stability and occasional clonal spreading in diploid C. amara, suggesting that nascent C. amara autotetraploid lineages were preadapted by their diploid lifestyle to survive while enduring reduced meiotic fidelity. However, in contrast to a lack of ortholog convergence, we see process-level and network convergence in DNA management, chromosome organisation, stress signalling, and ion homeostasis processes. This gives the first insight into the salient adaptations required to meet the challenges of a WGD state and shows that autopolyploids can utilize multiple evolutionary trajectories to adapt to WGD.

Transglutaminase 3: The Involvement in Epithelial Differentiation and Cancer

Transglutaminases (TGMs) contribute to the formation of rigid, insoluble macromolecular complexes, which are essential for the epidermis and hair follicles to perform protective and barrier functions against the environment. During differentiation, epidermal keratinocytes undergo structural alterations being transformed into cornified cells, which constitute a highly tough outermost layer of the epidermis, the stratum corneum. Similar processes occur during the hardening of the hair follicle and the hair shaft, which is provided by the enzymatic cross-linking of the structural proteins and keratin intermediate filaments. TGM3, also known as epidermal TGM, is one of the pivotal enzymes responsible for the formation of protein polymers in the epidermis and the hair follicle. Numerous studies have shown that TGM3 is extensively involved in epidermal and hair follicle physiology and pathology. However, the roles of TGM3, its substrates, and its importance for the integument system are not fully understood. Here, we summarize the main advances that have recently been achieved in TGM3 analyses in skin and hair follicle biology and also in understanding the functional role of TGM3 in human tumor pathology as well as the reliability of its prognostic clinical usage as a cancer diagnosis biomarker. This review also focuses on human and murine hair follicle abnormalities connected with TGM3 mutations.

Identifying adaptive alleles in the human genome: from selection mapping to functional validation

The suite of phenotypic diversity across geographically distributed human populations is the outcome of genetic drift, gene flow, and natural selection throughout human evolution. Human genetic variation underlying local biological adaptations to selective pressures is incompletely characterized. With the emergence of population genetics modeling of large-scale genomic data derived from diverse populations, scientists are able to map signatures of natural selection in the genome in a process known as selection mapping. Inferred selection signals further can be used to identify candidate functional alleles that underlie putative adaptive phenotypes. Phenotypic association, fine mapping, and functional experiments facilitate the identification of candidate adaptive alleles. Functional investigation of candidate adaptive variation using novel techniques in molecular biology is slowly beginning to unravel how selection signals translate to changes in biology that underlie the phenotypic spectrum of our species. In addition to informing evolutionary hypotheses of adaptation, the discovery and functional annotation of adaptive alleles also may be of clinical significance. While selection mapping efforts in non-European populations are growing, there remains a stark under-representation of diverse human populations in current public genomic databases, of both clinical and non-clinical cohorts. This lack of inclusion limits the study of human biological variation. Identifying and functionally validating candidate adaptive alleles in more global populations is necessary for understanding basic human biology and human disease.

Microfluidic platform for 3D cell culture with live imaging and clone retrieval

Combining live imaging with the ability to retrieve individual cells of interest remains a technical challenge. Combining imaging with precise cell retrieval is of particular interest when studying highly dynamic or transient, asynchronous, or heterogeneous cell biological and developmental processes. Here, we present a method to encapsulate live cells in a 3D hydrogel matrix, via hydrogel bead compartmentalisation. Using a small-scale screen, we optimised matrix conditions for the culture and multilineage differentiation of mouse embryonic stem cells. Moreover, we designed a custom microfluidic platform that is compatible with live imaging. With this platform we can long-term culture and subsequently extract individual cells-in-beads by media flow only, obviating the need for enzymatic cell removal from the platform. Specific beads may be extracted from the platform in isolation, without disrupting the adjacent beads. We show that we can differentiate mouse embryonic stem cells, monitor reporter expression by live imaging, and retrieve individual beads for functional assays, correlating reporter expression with functional response. Overall, we present a highly flexible 3D cell encapsulation and microfluidic platform that enables both monitoring of cellular dynamics and retrieval for molecular and functional assays.