Ancestral Relationships Research Articles

Inferring ancestry with the hierarchical soft clustering approach tangleGen.

Understanding the genetic ancestry of populations is central to numerous scientific and societal fields. It contributes to a better understanding of human evolutionary history, advances personalized medicine, aids in forensic identification, and allows individuals to connect to their genealogical roots. Existing methods, such as ADMIXTURE, have significantly improved our ability to infer ancestries. However, these methods typically work with a fixed number of independent ancestral populations. As a result, they provide insight into genetic admixture, but do not include a hierarchical interpretation. In particular, the intricate ancestral population structures remain difficult to unravel. Alternative methods with a consistent inheritance structure, such as hierarchical clustering, may offer benefits in terms of interpreting the inferred ancestries. Here, we present tangleGen, a soft clustering tool that transfers the hierarchical machine learning framework Tangles, which leverages graph theoretical concepts, to the field of population genetics. The hierarchical perspective of tangleGen on the composition and structure of populations improves the interpretability of the inferred ancestral relationships. Moreover, tangleGen adds a new layer of explainability, as it allows identifying the SNPs that are responsible for the clustering structure. We demonstrate the capabilities and benefits of tangleGen for the inference of ancestral relationships, using both simulated data and data from the 1000 Genomes Project.

KEARIFAN LOKAL BUDAYA MUNGGAH MOLO DAN KORELASINYA TERHADAP PANCASILA

ABSTACT the research of Munggah Molo culture as a cultural in Javanese culture during the construction of the house. To discover one of the cultures that still survive until today's era, analyzing of cultural values contained in munggah molo and its correlation with Pancasila. Cultural practices that reflect Pancasila values such as belief in God Almighty, Indonesian unity, just and civilized humanity, democracy, and social welfare. This culture also expresses concern for all parties participating as well as respect for cultural and national identity. Munggah molo has a meaning about the continuity between humans and the hope to have goodness in the house. Therefore, Munggah molo is not just a ritual, but contains deep meaning about ancestral relationships, harmonious social life, and respect for cultural and national values.

Genetic Insights into the Historical Attribution of Variety Names of Sweet Chestnut (Castanea sativa Mill.) in Northern Italy.

The sweet chestnut (Castanea sativa Mill.) is subject to the progressive disappearance of its traditional chestnut groves. In the northern part of Italy, where distribution of the sweet chestnut is fragmented, many local varieties continue to be identified mostly by oral tradition. We characterised by SSRs eleven historically recognised varieties of sweet chestnut in the area surrounding Lake Como, with the goal of giving a genetic basis to the traditional classification. We performed classical analysis about differentiation and used Bayesian approaches to detect population structure and to reconstruct demography. The results revealed that historical and genetic classifications are loosely linked when chestnut fruits are just "castagne", that is, normal fruits, but increasingly overlap where "marroni" (the most prized fruits) are concerned. Bayesian classification allowed us to identify a homogeneous gene cluster not recognised in the traditional assessment of the varieties and to reconstruct possible routes used for the propagation of sweet chestnut. We also reconstructed ancestral relationships between the different gene pools involved and dated ancestral lineages whose results fit with palynological data. We suggest that conservation strategies based on a genetic evaluation of the resource should also rely on traditional cultural heritage, which could reveal new sources of germplasm.

Joint inference of cell lineage and mitochondrial evolution from single-cell sequencing data.

Eukaryotic cells contain organelles called mitochondria that have their own genome. Most cells contain thousands of mitochondria which replicate, even in nondividing cells, by means of a relatively error-prone process resulting in somatic mutations in their genome. Because of the higher mutation rate compared to the nuclear genome, mitochondrial mutations have been used to track cellular lineage, particularly using single-cell sequencing that measures mitochondrial mutations in individual cells. However, existing methods to infer the cell lineage tree from mitochondrial mutations do not model "heteroplasmy," which is the presence of multiple mitochondrial clones with distinct sets of mutations in an individual cell. Single-cell sequencing data thus provide a mixture of the mitochondrial clones in individual cells, with the ancestral relationships between these clones described by a mitochondrial clone tree. While deconvolution of somatic mutations from a mixture of evolutionarily related genomes has been extensively studied in the context of bulk sequencing of cancer tumor samples, the problem of mitochondrial deconvolution has the additional constraint that the mitochondrial clone tree must be concordant with the cell lineage tree. We formalize the problem of inferring a concordant pair of a mitochondrial clone tree and a cell lineage tree from single-cell sequencing data as the Nested Perfect Phylogeny Mixture (NPPM) problem. We derive a combinatorial characterization of the solutions to the NPPM problem, and formulate an algorithm, MERLIN, to solve this problem exactly using a mixed integer linear program. We show on simulated data that MERLIN outperforms existing methods that do not model mitochondrial heteroplasmy nor the concordance between the mitochondrial clone tree and the cell lineage tree. We use MERLIN to analyze single-cell whole-genome sequencing data of 5220 cells of a gastric cancer cell line and show that MERLIN infers a more biologically plausible cell lineage tree and mitochondrial clone tree compared to existing methods. https://github.com/raphael-group/MERLIN.

Exploring the Accuracy and Limits of Algorithms for Localizing Recombination Breakpoints.

Phylogenetic methods are widely used to reconstruct the evolutionary relationships among species and individuals. However, recombination can obscure ancestral relationships as individuals may inherit different regions of their genome from different ancestors. It is, therefore, often necessary to detect recombination events, locate recombination breakpoints, and select recombination-free alignments prior to reconstructing phylogenetic trees. While many earlier studies have examined the power of different methods to detect recombination, very few have examined the ability of these methods to accurately locate recombination breakpoints. In this study, we simulated genome sequences based on ancestral recombination graphs and explored the accuracy of three popular recombination detection methods: MaxChi, 3SEQ, and Genetic Algorithm Recombination Detection. The accuracy of inferred breakpoint locations was evaluated along with the key factors contributing to variation in accuracy across datasets. While many different genomic features contribute to the variation in performance across methods, the number of informative sites consistent with the pattern of inheritance between parent and recombinant child sequences always has the greatest contribution to accuracy. While partitioning sequence alignments based on identified recombination breakpoints can greatly decrease phylogenetic error, the quality of phylogenetic reconstructions depends very little on how breakpoints are chosen to partition the alignment. Our work sheds light on how different features of recombinant genomes affect the performance of recombination detection methods and suggests best practices for reconstructing phylogenies based on recombination-free alignments.

Documentation of a novel FBP1 gene mutation in the Arabian ethnicity: a case report

BackgroundFructose-1,6-bisphosphatase deficiency is a rare autosomal recessive disorder characterized by impaired gluconeogenesis. Fructose-1,6-bisphosphatase 1 (FBP1) mutations demonstrate ethnic patterns. For instance, Turkish populations commonly harbor exon 2 deletions. We present a case report of whole exon 2 deletion in a Syrian Arabian child as the first recording of this mutation among Arabian ethnicity and the first report of FBP1 gene mutation in Syria.Case presentationWe present the case of a 2.5-year-old Syrian Arab child with recurrent hypoglycemic episodes, accompanied by nausea and lethargy. The patient’s history, physical examination, and laboratory findings raised suspicion of fructose-1,6-bisphosphatase deficiency. Whole exome sequencing was performed, revealing a homozygous deletion of exon 2 in the FBP1 gene, confirming the diagnosis.ConclusionThis case highlights a potential novel mutation in the Arab population; this mutation is well described in the Turkish population, which suggests potential shared mutations due to ancestral relationships between the two ethnicities. Further studies are needed to confirm this finding.

Population genomics provide insight into ancestral relationships and diversity of the feral horses of Theodore Roosevelt National Park.

Theodore Roosevelt National Park (TRNP) manages a herd of feral horses (Equus caballus) which was present on the landscape prior to the establishment of the park. The population presents a unique scenario in that it has experienced fairly intensive and well-documented management since the park's establishment, including herd size reductions, intentional introduction of diversity, and subsequent attempts to remove introduced lineages. This provides an interesting case study on the genetic effects of diverse evolutionary forces on an isolated feral population. To explore the effects of these forces and clarify the relationship of this feral herd with other horses, we used genome-wide markers to examine the population structure of a combined dataset containing common established breeds. Using the Illumina Equine 70k BeadChip, we sampled SNPs across the genome for 118 TRNP horses and evaluated the inbreeding coefficient f and runs of homozygosity (RoH). To identify breed relationships, we compared 23 representative TRNP samples with 792 horses from 35 different breeds using genomic population structure analyses. Mean f of TRNP horses was 0.180, while the mean f for all other breeds in the dataset was 0.116 (SD 0.079). RoH analysis indicates that the TRNP population has experienced recent inbreeding in a timeframe consistent with their management. With Bayesian clustering, PCA, and maximum likelihood phylogeny, TRNP horses show genetic differentiation from other breeds, likely due to isolation, historical population bottlenecks, and genetic drift. However, maximum likelihood phylogeny places them with moderate confidence (76.8%) among draft breeds, which is consistent with the known history of breeds used on early North Dakota ranches and stallions subsequently introduced to the park herd. These findings will help resolve speculation about the origins of the herd and inform management decisions for the TRNP herd.

Abstract PR009: Tick tock trees: Reconstructing the evolutionary dynamics of human tissues using fluctuating methylation clocks

Abstract The development of cancer from healthy somatic cells is fundamentally an evolutionary process. Understanding this process is vital to improving its clinical management and developing new treatment strategies. Tracing individual human cells’ fates would simultaneously advance somatic evolutionary theory and our understanding of normal tissue function and its change through development, aging, and cancer progression. We cannot use human cell-labeling techniques in vivo. Still, population genetic and phylogenetic models can leverage the information recorded in heritable alterations to reconstruct the unobserved somatic cells’ history. Most such methods are limited by the few parameters they can estimate and restricted to neoplastic samples due to the lack of adequate evolutionary signal in healthy somatic cells. Gabbutt et al. recently ameliorated this limitation by introducing fluctuating methylation clocks (FMCs)—tissue-specific CpG sites that randomly change their methylation state—and a model that uses them to reconstruct the evolution of a clonal stem-cell population. In this application, all FMCs in a bulk sample are interrogated using a single standard methylation array to yield estimates of rates of methylation, demethylation and cell replacement, and the size of the stem-cell niche. This technique is especially suited to studying stem-cell niche dynamics in healthy or pre-malignant tissues organized in clonal cell populations where the whole population can be sampled together, like crypts (e.g., intestine, Barrett’s esophagus) and glands (e.g., endometrium). We have developed a multi-sample extension of this model that simultaneously reconstructs the evolutionary dynamics of stem cells within a niche and the niches within the tissue. This phylodynamic model produces additional estimates like ancestral relationships between sampled clonal populations, their calendar divergence times, the number of effective evolutionary niches, and how some of these parameters change over time. Here, we will present the method, demonstrate its validity, characterize its accuracy under a broad simulation parameter space, and showcase its application in analyzing human data from the following tissues: colon, small intestine, endometrium, and Barrett’s esophagus. We will also discuss the current model's limitations and future improvements that will discern between mechanisms of stem-cell-niche reproduction and incorporate geographical information. The stochastic nature of neoplastic progression makes it unlikely for any particular somatic alteration to be highly predictive of its outcome. This can explain why developing reliable traditional biomarkers has been so difficult. Alternatively, evolutionary biomarkers measure the characteristics of the process itself and thus should apply to all neoplasms. Parametric phylogenetic reconstruction models like the one introduced here will enable us to develop such universal biomarkers. Our ultimate goal is for evolutionary biomarkers to join evolutionary therapies in the revolution of the clinical management of cancer. Citation Format: Diego Mallo, Pablo Bousquets-Muñoz, Heather E. Grant, Darryl Shibata, Trevor A. Graham, Carlo C. Maley, Calum Gabbutt. Tick tock trees: Reconstructing the evolutionary dynamics of human tissues using fluctuating methylation clocks [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr PR009.

Mana Moana

Our article is an investigation of the architectural meanings of Moana when located in Aotearoa, as Pacific practitioners, designers, and academics. This article will traverse sensitive topics, such as how Aotearoa’s Pacific peoples relate to Tangata Whenua today and how this is expressed in the built space. How can we navigate Te Tiriti o Waitangi through our voyaging histories, moving beyond the muddy relations within urban conditions in Aotearoa? The phrase Mana Moana is used to refer to the ancestral relationships between Tangata Whenua and the wider Moana, or vast Pacific region, as a positioning framework for our discussions. Mana Moana reinforces connected genealogies of Māori and Pacific peoples across deep time and space beyond the shores of Aotearoa, New Zealand. The article draws on architectural case studies from Aotearoa that investigate placemaking concepts and praxes that provoke, educate, and inspire current and future built environments of Aotearoa, New Zealand.

MAGE: metafounders-assisted genomic estimation of breeding value, a novel additive-dominance single-step model in crossbreeding systems.

Utilizing both purebred and crossbred data in animal genetics is widely recognized as an optimal strategy for enhancing the predictive accuracy of breeding values. Practically, the different genetic background among several purebred populations and their crossbred offspring populations limits the application of traditional prediction methods. Several studies endeavor to predict the crossbred performance via the partial relationship, which divides the data into distinct sub-populations based on the common genetic background, such as one single purebred population and its corresponding crossbred descendant. However, this strategy makes prediction inaccurate due to ignoring half of the parental information of crossbreed animals. Furthermore, dominance effects, although playing a significant role in crossbreeding systems, cannot be modeled under such a prediction model. To overcome this weakness, we developed a novel multi-breed single-step model using metafounders to assess ancestral relationships across diverse breeds under a unified framework. We proposed to use multi-breed dominance combined relationship matrices to model additive and dominance effects simultaneously. Our method provides a straightforward way to evaluate the heterosis of crossbreeds and the breeding values of purebred parents efficiently and accurately. We performed simulation and real data analyses to verify the potential of our proposed method. Our proposed model improved prediction accuracy under all scenarios considered compared to commonly used methods. The software for implementing our method is available at https://github.com/CAU-TeamLiuJF/MAGE.

Readings on Evolution and the Nature of Science: One Christian’s Perspective

Readings on Evolution and the Nature of Science: One Christian’s Perspective

Where to draw the boundaries? Using landscape genomics to disentangle the scribbly gum species complex.

Species delimitation is an integral part of evolution and ecology and is vital in conservation science. However, in some groups, species delimitation is difficult, especially where ancestral relationships inferred from morphological or genetic characters are discordant, possibly due to a complicated demographic history (e.g., recent divergences between lineages). Modern genetic techniques can take into account complex histories to distinguish species at a reasonable cost and are increasingly used in numerous applications. We focus on the scribbly gums, a group of up to five closely related and morphologically similar "species" within the eucalypts. Multiple populations of each recognized scribbly gum species were sampled over a wide region across climates, and genomewide scans were used to resolve species boundaries. None of the taxa were completely divergent, and there were two genetically distinct entities: the inland distributed Eucalyptus rossii and a coastal conglomerate consisting of four species forming three discernible, but highly admixed groups. Divergence among taxa was likely driven by temporal vicariant processes resulting in partial separation across biogeographic barriers. High interspecific gene flow indicated separated taxa reconnected at different points in time, blurring species boundaries. Our results highlight the need for genetic screening when dealing with closely related taxonomic entities, particularly those with modest morphological differences. We show that high-throughput sequencing can be effective at identifying species groupings and processes driving divergence, even in the most taxonomically complex groups, and be used as a standard practice for disentangling species complexes.

Graph-Theoretical Analysis of Biological Networks: A Survey

Biological networks such as protein interaction networks, gene regulation networks, and metabolic pathways are examples of complex networks that are large graphs with small-world and scale-free properties. An analysis of these networks has a profound effect on our understanding the origins of life, health, and the disease states of organisms, and it allows for the diagnosis of diseases to aid in the search for remedial processes. In this review, we describe the main analysis methods of biological networks using graph theory, by first defining the main parameters, such as clustering coefficient, modularity, and centrality. We then survey fundamental graph clustering methods and algorithms, followed by the network motif search algorithms, with the aim of finding repeating subgraphs in a biological network graph. A frequently appearing subgraph usually conveys a basic function that is carried out by that small network, and discovering such a function provides an insight into the overall function of the organism. Lastly, we review network alignment algorithms that find similarities between two or more graphs representing biological networks. A conserved subgraph between the biological networks of organisms may mean a common ancestor, and finding such a relationship may help researchers to derive ancestral relationships and to predict the future evolution of organisms to enable the design of new drugs. We provide a review of the research studies in all of these methods, and conclude using the current challenging areas of biological network analysis, and by using graph theory and parallel processing for high performance analysis.

New algorithm for the analysis of nucleotide and amino acid evolutionary relationships based on Klein four-group

Phylogenetics is the study of ancestral relationships among biological species. Such sequence analyses are often represented as phylogenetic trees. The branching pattern of each tree and its topology reflect the evolutionary relatedness between analyzed sequences. We present a Klein four-group algorithm (K4A) for the evolutionary analysis of nucleotide and amino acid sequences. Klein four-group set of operators consists of: identity e (U), and three elements—a = transition (C), b = transversion (G) and c = transition-transversion or complementarity (A). We generated Klein four-group based distance matrices of: 1. Cayley table (CK4), 2. Table rows (K4R), 3. Table columns (K4C), and 4. Euclidean 2D distance (K4E). The performance of the matrices was tested on a dataset of RecA proteins in bacteria, eukaryotes (Rad51 homolog) and archaea (RadA homolog). RecA and its functional homologs are found in all species, and are essential for the repair and maintenance of DNA. Consequently, they represent a good model for the study of evolutionary relationship of protein and nucleotide sequences. The ancestral relationship between the sequences was correctly classified by all K4A matrices concerning general topology. All distance matrices exhibited small variations among species, and overall results of tree classification were in agreement with the general patterns obtained by standard BLOSUM and PAM substitution matrices. During the evolution of a code there is a phase of optimization of system rules, the ambiguity of a code is eliminated, and the system starts producing specific components. Klein four-group algorithm is consistent with the concept of ambiguity reduction. It also enables the use of different genetic code table variants optimized for particular transitions in evolution based on biological specificity.

Agri-silvicultures of Mexican Arid America

BackgroundAgri-silvicultures (ASC) are biocultural practices procuring either the maintenance of wild diversity in predominantly agricultural spaces or introducing agrobiodiversity into forests. In the Mesoamerican region, ASC contribute to food sovereignty and territorial conservation and provide strategies for dealing with global changes. Previous inventories of ASC identified gaps in information about these systems in the Mexican Arid America region. This article raises the general question: How have human interactions between cultural, wild, and domesticated biodiversity in this territory? The particular questions in this paper are: (i) How have historical processes shaped human interactions between wild and domesticated biodiversity in the region? and (ii) What types of agri-silvicultures have emerged in Mexican Arid America since these relationships?MethodsWe trace a methodological border where archaeologists have identified the Mesoamerican region to define our study area as Arid America northern of this line in Mexico. We analyzed agriculturalization processes in Arid America through a historical review. Then, we carry out an inventory of Arid America ASC based on academic papers and other documented experiences. We constructed a spatial database and a typology to understand what kinds of agri-silviculture occur in the region.ResultsWe identified several pre-Hispanic agri-silvicultural practices in the region, like hunting, fishing, terraces, gathering, and irrigation systems. The cultivation of native species of maize, beans, and squash even was registered. The Spanish colonization forced the agriculturization in arid northern Mexico, where itinerant hunting-gathering patterns predominated. In the twentieth century, the Green Revolution adopted this area as the principal setting for industrialized agriculture. The industrialized irrigated systems expansion and other political strategies provoked the simplification of productive landscapes. The practices that integrate wild and agricultural diversity systems were marginalized and invisibilized in such a context. Our research group proposes seven types of agri-silvicultural systems (natives agrisilvicultures, the oases agroforestry, Mesquite and Huisache ASC, homegardens and other traditional forms of agroforestry or agri-silvicultures). These agri-silvicultures provide food, medicine, fodder, and other contributions, as income to the families that practice them and protect native and exotic species.Discussion and conclusionThe agriculturization of the arid environments initiated during Spanish colonization and the subsequent modernizing projects shaped dominant actors and ideologies in the arid north of Mexico. However, aridity has favored ancestral and agroecological relationships between cultures and biodiversity, emerging and subsisting Arid American agri-silvicultures. These agri-silvicultures deserve to be understood, adopted, and adapted to new contexts. They could be essential alternatives in the context of environmental changes.

The transhistorical, transcultural life of sausages: From medieval morescas to New Mexican Matachines with Aby Warburg

New Mexican Matachines dances have long been discussed as descendent dances of medieval morescas. This article explores this ‘ancestral relation’, beginning on New Year’s Day in 1896 at the colonial outpost of Cubero, New Mexico. There, the German art historian Aby Warburg met a local shepherd who endeavoured to explain the pantomimic killing of a bull in the dance drama by saying the blood was ‘good for making sausages.’ Accordingly, this article investigates Warburg’s lifelong exploration of Matachines antecedents in the margins of his research on early Italian Renaissance images of medieval festive drama, and ‘headhuntress’ figures, such as Judith and Salome. Warburg’s thoughts on New Mexican Matachines meandered over the course of his life from Aztec sacrifice to medieval morescas, to the Mithras cult. Through these explorations, Warburg pursued a cultural evolutionary theory that would situate New Mexican Matachines as a descendent of antique pagan blood ceremony.

Molecular Evolution of Aryl Hydrocarbon Receptor Signaling Pathway Genes.

The Aryl hydrocarbon receptor is an ancient transcriptional factor originally discovered as a sensor of dioxin. In addition to its function as a receptor of environmental toxicants, it plays an important role in development. Although a significant amount of research has been carried out to understand the AHR signal transduction pathway and its involvement in species' susceptibility to environmental toxicants, none of them to date has comprehensively studied its evolutionary origins. Studying the evolutionary origins of molecules can inform ancestral relationships of genes. The vertebrate genome has been shaped by two rounds of whole-genome duplications (WGD) at the base of vertebrate evolution approximately 600 million years ago, followed by lineage-specific gene losses, which often complicate the assignment of orthology. It is crucial to understand the evolutionary origins of this transcription factor and its partners, to distinguish orthologs from ancient non-orthologous homologs. In this study, we have investigated the evolutionary origins of proteins involved in the AHR pathway. Our results provide evidence of gene loss and duplications, crucial for understanding the functional connectivity of humans and model species. Multiple studies have shown that 2R-ohnologs (genes and proteins that have survived from the 2R-WGD) are enriched in signaling components relevant to developmental disorders and cancer. Our findings provide a link between the AHR pathway's evolutionary trajectory and its potential mechanistic involvement in pathogenesis.

Shared pedigree relationships and transmission of unreduced gametes in cultivated banana.

Cultivated bananas resulted from inter(sub)specific hybridizations involving Musa species and subspecies (M. acuminata subspecies, M. schizocarpa, M. balbisiana) and the subsequent selection, centuries ago, of hybrids with parthenocarpic, seedless fruits. Cultivars have low fertility and are vegetatively propagated, forming groups of somaclones. Relatively few of them, mainly triploids, are grown on a large scale and characterization of their parental relationships may be useful for breeding strategies. Here we investigate parental relationships and gamete-type contributions among diploid and polyploid banana cultivars. We used SNP genotyping data from whole-genome sequencing of 178 banana individuals, including 111 cultivars, 55 wild bananas and 12 synthetic F1 hybrids. We analysed the proportion of SNP sites in accordance with direct parentage with a global statistic and along chromosomes for selected individuals. We characterized parentage relationships for 7 diploid cultivars, 11 triploid cultivars and 1 tetraploid cultivar. Results showed that both diploid and triploid cultivars could have contributed gametes to other banana cultivars. Diploids may have contributed 1x or 2x gametes and triploids 1x to 3x gametes. The Mchare diploid cultivar group, nowadays only found in East Africa, was found as parent of two diploid and eight triploid cultivars. In five of its identified triploid offspring, corresponding to main export or locally popular dessert bananas, Mchare contributed a 2x gamete with full genome restitution without recombination. Analyses of remaining haplotypes in these Mchare offspring suggested ancestral pedigree relationships between different interspecific banana cultivars. The current cultivated banana resulted from different pathways of formation, with implication of recombined or un-recombined unreduced gametes produced by diploid or triploid cultivars. Identification of dessert banana's parents and the types of gametes they contributed should support the design of breeding strategies.

Genomic prediction with haplotype blocks in wheat.

Haplotype blocks might carry additional information compared to single SNPs and have therefore been suggested for use as independent variables in genomic prediction. Studies in different species resulted in more accurate predictions than with single SNPs in some traits but not in others. In addition, it remains unclear how the blocks should be built to obtain the greatest prediction accuracies. Our objective was to compare the results of genomic prediction with different types of haplotype blocks to prediction with single SNPs in 11 traits in winter wheat. We built haplotype blocks from marker data from 361 winter wheat lines based on linkage disequilibrium, fixed SNP numbers, fixed lengths in cM and with the R package HaploBlocker. We used these blocks together with data from single-year field trials in a cross-validation study for predictions with RR-BLUP, an alternative method (RMLA) that allows for heterogeneous marker variances, and GBLUP performed with the software GVCHAP. The greatest prediction accuracies for resistance scores for B. graminis, P. triticina, and F. graminearum were obtained with LD-based haplotype blocks while blocks with fixed marker numbers and fixed lengths in cM resulted in the greatest prediction accuracies for plant height. Prediction accuracies of haplotype blocks built with HaploBlocker were greater than those of the other methods for protein concentration and resistances scores for S. tritici, B. graminis, and P. striiformis. We hypothesize that the trait-dependence is caused by properties of the haplotype blocks that have overlapping and contrasting effects on the prediction accuracy. While they might be able to capture local epistatic effects and to detect ancestral relationships better than single SNPs, prediction accuracy might be reduced by unfavorable characteristics of the design matrices in the models that are due to their multi-allelic nature.

Insertion and deletion mutations preserved in SARS-CoV-2 variants.

The insertion/deletion (indel) mutation profiles of SARS-CoV-2 variants, including Omicron, remain unclear. We compared whole-genome sequences from various lineages and used preserved indels to infer the ancestral relationships between different lineages. Thirteen indel patterns from twelve sites were seen in ≥ 2 sequences; six of these sites were located in the N-terminal domain of the viral spike gene. Preserved indels in the coding regions were also identified in the non-structural protein 3 (Nsp3), Nsp6, and nucleocapsid genes. Seven of the thirteen indel patterns were specific to the Omicron variants, four of which were observed in BA.1, making it the most mutated variant. Other preserved indels observed in the Omicron variants were also seen in Alpha and/or Gamma, but not Delta, suggesting that Omicron is phylogenetically more proximal to Alpha. We demonstrated distinct profiles of preserved indels among SARS-CoV-2 variants and sublineages, suggesting the importance of indels in viral evolution.