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We report on the sequencing of 10,545 human genomes at 30×–40× coverage with an emphasis on quality metrics and novel variant and sequence discovery. We find that 84% of an individual human genome can be sequenced confidently. This high-confidence region includes 91.5% of exon sequence and 95.2% of known pathogenic variant positions. We present the distribution of over 150 million single-nucleotide variants in the coding and noncoding genome. Each newly sequenced genome contributes an average of 8,579 novel variants. In addition, each genome carries on average 0.7 Mb of sequence that is not found in the main build of the hg38 reference genome. The density of this catalog of variation allowed us to construct high-resolution profiles that define genomic sites that are highly intolerant of genetic variation. These results indicate that the data generated by deep genome sequencing is of the quality necessary for clinical use.

KEY MESSAGE : Genetic diversity and population structure in the US Upland cotton was established and core sets of allelic richness were identified for developing association mapping populations in cotton. Elite plant breeding programs could likely benefit from the unexploited standing genetic variation of obsolete cultivars without the yield drag typically associated with wild accessions. A set of 381 accessions comprising 378 Upland (Gossypium hirsutum L.) and 3 G. barbadense L. accessions of the United States cotton belt were genotyped using 120 genome-wide SSR markers to establish the genetic diversity and population structure in tetraploid cotton. These accessions represent more than 100 years of Upland cotton breeding in the United States. Genetic diversity analysis identified a total of 546 alleles across 141 marker loci. Twenty-two percent of the alleles in Upland accessions were unique, specific to a single accession. Population structure analysis revealed extensive admixture and identified five subgroups corresponding to Southeastern, Midsouth, Southwest, and Western zones of cotton growing areas in the United States, with the three accessions of G. barbadense forming a separate cluster. Phylogenetic analysis supported the subgroups identified by STRUCTURE. Average genetic distance between G. hirsutum accessions was 0.195 indicating low levels of genetic diversity in Upland cotton germplasm pool. The results from both population structure and phylogenetic analysis were in agreement with pedigree information, although there were a few exceptions. Further, core sets of different sizes representing different levels of allelic richness in Upland cotton were identified. Establishment of genetic diversity, population structure, and identification of core sets from this study could be useful for genetic and genomic analysis and systematic utilization of the standing genetic variation in Upland cotton.

This study describes efforts to define and protect traditional knowledge and the associated issues of access to genetic resources, from the negotiation of the Convention on Biological Diveristy through to the Declaration of Rights of Indigenous Peoples and the Nagoya Protocol.

A comprehensive genetic diversity analysis of 87 Passiflora germplasm accessions domesticated and cultivated for several years in the karst region of Guizhou, China, was conducted utilizing simple sequence repeat (SSR) fluorescent markers. These Passiflora species, renowned for their culinary and medicinal value, could bring significant economic and ecological benefits to the region. This study aimed to assess the genetic resources of these species and facilitate the selection of superior cultivars adapted to the karst environment. Our analysis revealed an abundance of SSR loci within the Passiflora transcriptome, with single-base repeats being the most prevalent type. Through rigorous primer screening and amplification, we successfully identified 27 SSR primer pairs exhibiting robust polymorphisms. Further interrogation at eight microsatellite loci revealed 68 alleles, underscoring the high level of genetic diversity present in the cultivated accessions. The average expected heterozygosity was 0.202, with the ssr18 locus exhibiting the highest value of 0.768, indicating significant genetic variation. The mean polymorphic information content (PIC) of 0.657 indicates the informativeness of these SSR markers. Comparative analyses of the cultivated and potential wild progenitors revealed distinct genetic variations among the different Passiflora types. Genetic structure and clustering analyses of the 87 accessions revealed seven distinct groups, suggesting gene flow and similarities among the resources. Notably, a DNA fingerprinting system was established using eight SSR primer pairs, effectively distinguishing the selected cultivars that had adapted to the karst mountainous region. This study not only deepens our understanding of Passiflora genetic resources in the karst environment but also provides a valuable reference for conservation, genetic improvement, and cultivar selection. The rich genetic diversity of the Passiflora germplasm underscores their potential for sustainable utilization in breeding programs aimed at enhancing the economic and ecological viability of these valuable plant species.

The genus Polygonatum encompasses numerous species with complex phenotypes, necessitating robust molecular markers for accurate species identification and superior germplasm screening. This study identified and developed SSR markers based on transcriptome analysis of three Polygonatum species to assess the genetic diversity of Polygonatum resources. The results showed that a total of 43,217 SSR loci were detected, and 31,703 primer pairs were successfully designed. Characterization of SSR motifs revealed mono-nucleotide repeats (SNRs) were the most frequent (59.45%). Unigenes containing SSRs were annotated across seven databases. In KEGG, 222 pathways were assigned, with genes annotated to carbohydrate metabolism being the most abundant. To validate and apply these markers, 100 primer pairs covering all eight SSR locus types were tested across 21 Polygonatum accessions. Of these, 49 polymorphic markers were identified, revealing high genetic diversity, with average expected heterozygosity (He) and polymorphism information content (PIC) values of 0.763 and 0.718, respectively, alongside significant population differentiation (Fst = 0.307). Cluster analysis grouped 21 accessions into three groups, which correlated with certain agronomic traits. Nine core markers were selected that effectively distinguished six species and intraspecific groups. Notably, the FB-9 marker, associated with polysaccharide biosynthesis, effectively discriminated among six Polygonatum species and also distinguished distinct germplasm resources within P. kingianum var. grandifolium. Overall, the transcriptome-derived SSR markers validated in this study constitute valuable resources for gene function analysis, population genetics research, and variety identification and genetic improvement of Polygonatum.

Aim The use of genetic analyses has become ubiquitous in conservation planning and management. Typically, such analyses are employed at the species‐level, though as genetic data accrue, it is now possible to consider the genetic composition of multiple species across landscapes. Such macrogenetic perspectives can reveal the potential genetic ramifications of extreme disturbance events, such as the catastrophic Australian ‘Black Summer' wildfires of 2019–2020. Here, we present a framework to examine the potential genetic impacts of this event upon populations of a variety of taxa. Location Eastern Australia. Methods Using hundreds of samples spanning dozens of frog, mammal and reptile species, we demonstrate a macrogenetic approach for using reduced‐representation sequencing data from several species to describe the fine‐scale distribution of genetic diversity across a landscape in a robust, comparable manner. We do so using standard population genetics metrics (heterozygosity); though we also propose a novel complementary measure—‘weighted distinctiveness’—to identify important regions of the landscape where narrowly distributed and evolutionarily distinct populations from multiple species reside. Results Although variable across the study area, we show that these unprecedented fires generally burned areas where genetic diversity of sampled taxa was higher than that of areas remaining unburned. Additionally, regions harbouring high concentrations of evolutionarily distinct and narrowly distributed species were disproportionately represented in burned regions, with the potential cross‐taxonomic adverse effects being greatest in Australia's southeast and central eastern seaboard regions. Main Conclusions Our findings suggest that the macrogenetic impacts of the Black Summer wildfires have the potential to have been more severe than initially apparent. Importantly, they also demonstrate how conservation genetics principles often applied at a species level can be expanded to landscapes, whilst accounting for the challenges that arise when aggregating across taxonomic groups, thereby improving our understanding of the overall impacts of large‐scale disturbance events.

Biological functions are typically performed by groups of cells that express predominantly the same genes, yet display a continuum of phenotypes. While it is known how one genotype can generate such non‐genetic diversity, it remains unclear how different phenotypes contribute to the performance of biological function at the population level. We developed a microfluidic device to simultaneously measure the phenotype and chemotactic performance of tens of thousands of individual, freely swimming Escherichia coli as they climbed a gradient of attractant. We discovered that spatial structure spontaneously emerged from initially well‐mixed wild‐type populations due to non‐genetic diversity. By manipulating the expression of key chemotaxis proteins, we established a causal relationship between protein expression, non‐genetic diversity, and performance that was theoretically predicted. This approach generated a complete phenotype‐to‐performance map, in which we found a nonlinear regime. We used this map to demonstrate how changing the shape of a phenotypic distribution can have as large of an effect on collective performance as changing the mean phenotype, suggesting that selection could act on both during the process of adaptation. Synopsis A bacterial “race” in a microfluidic device revealed non‐genetic diversity in behavior and performance of clonal E. coli cells. The “shape” of behavioral diversity affected population performance as much as the mean behavior, supporting the hypothesis that this shape is evolvable. A new microfluidic device was designed and used to track and analyze the trajectories of tens of thousands of individual, freely swimming bacteria climbing a gradient of chemoattractant. Clonal wild‐type populations featured substantial behavioral diversity, giving rise to differences in performance that caused populations of bacteria to spatially segregate by phenotype as they climbed a gradient of attractant. Manipulating gene expression of key chemotaxis proteins changed population phenotype and consequently performance, establishing a causal relationship between gene expression, phenotypic distribution, and population performance. The population outperformed its mean phenotype due to the nonlinear shape of the phenotype‐to‐performance function, which disproportionately amplified the contributions of the tail of the phenotype distribution. Thus, the shape of a phenotypic distribution can be as important in determining population performance as its mean. Graphical Abstract A bacterial “race” in a microfluidic device revealed non‐genetic diversity in behavior and performance of clonal E. coli cells. The “shape” of behavioral diversity affected population performance as much as the mean behavior, supporting the hypothesis that this shape is evolvable.

Background In sub-Saharan Africa (SSA), Plasmodium falciparum causes most of the malaria cases. Despite its crucial roles in disease severity and drug resistance, comprehensive data on Plasmodium falciparum genetic diversity and multiplicity of infection (MOI) are sparse in SSA. This study summarizes available information on genetic diversity and MOI, focusing on key markers ( msp-1, msp-2, glurp , and microsatellites). The systematic review aimed to evaluate their influence on malaria transmission dynamics and offer insights for enhancing malaria control measures in SSA. Methods The review was conducted following the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines. Two reviewers conducted article screening, assessed the risk of bias (RoB), and performed data abstraction. Meta-analysis was performed using the random-effects model in STATA version 17. Results The review included 52 articles: 39 cross-sectional studies and 13 Randomized Controlled Trial (RCT)/cohort studies, involving 11,640 genotyped parasite isolates from 23 SSA countries. The overall pooled mean expected heterozygosity was 0.65 (95% CI: 0.51–0.78). Regionally, values varied: East (0.58), Central (0.84), Southern (0.74), and West Africa (0.69). Overall pooled allele frequencies of msp-1 alleles K1, MAD20, and RO33 were 61%, 44%, and 40%, respectively, while msp-2 I/C 3D7 and FC27 alleles were 61% and 55%. Central Africa reported higher frequencies (K1: 74%, MAD20: 51%, RO33: 48%) than East Africa (K1: 46%, MAD20: 42%, RO33: 31%). For msp-2 , East Africa had 60% and 55% for I/C 3D7 and FC27 alleles, while West Africa had 62% and 50%, respectively. The pooled allele frequency for glurp was 66%. The overall pooled mean MOI was 2.09 (95% CI: 1.88–2.30), with regional variations: East (2.05), Central (2.37), Southern (2.16), and West Africa (1.96). The overall prevalence of polyclonal Plasmodium falciparum infections was 63% (95% CI: 56–70), with regional prevalences as follows: East (62%), West (61%), Central (65%), and South Africa (71%). Conclusion The study shows substantial regional variation in Plasmodium falciparum parasite genetic diversity and MOI in SSA. These findings suggest a need for malaria control strategies and surveillance efforts considering regional-specific factors underlying Plasmodium falciparum infection.