Explore the vast range of titles available.

Genome-wide association (GWA) is gaining popularity as a means to study the architecture of complex quantitative traits, partially due to the improvement of high-throughput low-cost genotyping and phenotyping technologies. Glucosinolate (GSL) secondary metabolites within Arabidopsis spp. can serve as a model system to understand the genomic architecture of adaptive quantitative traits. GSL are key anti-herbivory defenses that impart adaptive advantages within field trials. While little is known about how variation in the external or internal environment of an organism may influence the efficiency of GWA, GSL variation is known to be highly dependent upon the external stresses and developmental processes of the plant lending it to be an excellent model for studying conditional GWA. To understand how development and environment can influence GWA, we conducted a study using 96 Arabidopsis thaliana accessions, >40 GSL phenotypes across three conditions (one developmental comparison and one environmental comparison) and ∼230,000 SNPs. Developmental stage had dramatic effects on the outcome of GWA, with each stage identifying different loci associated with GSL traits. Further, while the molecular bases of numerous quantitative trait loci (QTL) controlling GSL traits have been identified, there is currently no estimate of how many additional genes may control natural variation in these traits. We developed a novel co-expression network approach to prioritize the thousands of GWA candidates and successfully validated a large number of these genes as influencing GSL accumulation within A. thaliana using single gene isogenic lines. Together, these results suggest that complex traits imparting environmentally contingent adaptive advantages are likely influenced by up to thousands of loci that are sensitive to fluctuations in the environment or developmental state of the organism. Additionally, while GWA is highly conditional upon genetics, the use of additional genomic information can rapidly identify causal loci en masse.

Anatomically modern humans originated in Africa around 200 thousand years ago (ka) 1 – 4 . Although some of the oldest skeletal remains suggest an eastern African origin 2 , southern Africa is home to contemporary populations that represent the earliest branch of human genetic phylogeny 5 , 6 . Here we generate, to our knowledge, the largest resource for the poorly represented and deepest-rooting maternal L0 mitochondrial DNA branch (198 new mitogenomes for a total of 1,217 mitogenomes) from contemporary southern Africans and show the geographical isolation of L0d1’2, L0k and L0g KhoeSan descendants south of the Zambezi river in Africa. By establishing mitogenomic timelines, frequencies and dispersals, we show that the L0 lineage emerged within the residual Makgadikgadi–Okavango palaeo-wetland of southern Africa 7 , approximately 200 ka (95% confidence interval, 240–165 ka). Genetic divergence points to a sustained 70,000-year-long existence of the L0 lineage before an out-of-homeland northeast–southwest dispersal between 130 and 110 ka. Palaeo-climate proxy and model data suggest that increased humidity opened green corridors, first to the northeast then to the southwest. Subsequent drying of the homeland corresponds to a sustained effective population size (L0k), whereas wet–dry cycles and probable adaptation to marine foraging allowed the southwestern migrants to achieve population growth (L0d1’2), as supported by extensive south-coastal archaeological evidence 8 – 10 . Taken together, we propose a southern African origin of anatomically modern humans with sustained homeland occupation before the first migrations of people that appear to have been driven by regional climate changes. Analyses of mitochondrial genomes from populations in southern Africa provide evidence of a southern African origin of anatomically modern humans and a sustained occupation of the homeland before the first migrations of people appear to be driven by regional climate shifts.

Despite the described central role of jasmonate signaling in plant defense against necrotrophic pathogens, the existence of intraspecific variation in pathogen capacity to activate or evade plant jasmonate-mediated defenses is rarely considered. Experimental infection of jasmonate-deficient and jasmonate-insensitive Arabidopsis thaliana with diverse isolates of the necrotrophic fungal pathogen Botrytis cinerea revealed pathogen variation for virulence inhibition by jasmonate-mediated plant defenses and induction of plant defense metabolites. Comparison of the transcriptional effects of infection by two distinct B. cinerea isolates showed only minor differences in transcriptional responses of wild-type plants, but notable isolate-specific transcript differences in jasmonate-insensitive plants. These transcriptional differences suggest B. cinerea activation of plant defenses that require plant jasmonate signaling for activity in response to only one of the two B. cinerea isolates tested. Thus, similar infection phenotypes observed in wild-type plants result from different signaling interactions with the plant that are likely integrated by jasmonate signaling.

Discovering links between the genotype of an organism and its metabolite levels can increase our understanding of metabolism, its controls, and the indirect effects of metabolism on other quantitative traits. Recent technological advances in both DNA sequencing and metabolite profiling allow the use of broad-spectrum, untargeted metabolite profiling to generate phenotypic data for genome-wide association studies that investigate quantitative genetic control of metabolism within species. We conducted a genome-wide association study of natural variation in plant metabolism using the results of untargeted metabolite analyses performed on a collection of wild Arabidopsis thaliana accessions. Testing 327 metabolites against >200,000 single nucleotide polymorphisms identified numerous genotype-metabolite associations distributed non-randomly within the genome. These clusters of genotype-metabolite associations (hotspots) included regions of the A. thaliana genome previously identified as subject to recent strong positive selection (selective sweeps) and regions showing trans-linkage to these putative sweeps, suggesting that these selective forces have impacted genome-wide control of A. thaliana metabolism. Comparing the metabolic variation detected within this collection of wild accessions to a laboratory-derived population of recombinant inbred lines (derived from two of the accessions used in this study) showed that the higher level of genetic variation present within the wild accessions did not correspond to higher variance in metabolic phenotypes, suggesting that evolutionary constraints limit metabolic variation. While a major goal of genome-wide association studies is to develop catalogues of intraspecific variation, the results of multiple independent experiments performed for this study showed that the genotype-metabolite associations identified are sensitive to environmental fluctuations. Thus, studies of intraspecific variation conducted via genome-wide association will require analyses of genotype by environment interaction. Interestingly, the network structure of metabolite linkages was also sensitive to environmental differences, suggesting that key aspects of network architecture are malleable.

The oldest extant human maternal lineages include mitochondrial haplogroups L0d and L0k found in the southern African click-speaking forager peoples broadly classified as Khoesan. Profiling these early mitochondrial lineages allows for better understanding of modern human evolution. In this study, we profile 77 new early-diverged complete mitochondrial genomes and sub-classify another 105 L0d/L0k individuals from southern Africa. We use this data to refine basal phylogenetic divergence, coalescence times and Khoesan prehistory. Our results confirm L0d as the earliest diverged lineage (∼172 kya, 95%CI: 149-199 kya), followed by L0k (∼159 kya, 95%CI: 136-183 kya) and a new lineage we name L0g (∼94 kya, 95%CI: 72-116 kya). We identify two new L0d1 subclades we name L0d1d and L0d1c4/L0d1e, and estimate L0d2 and L0d1 divergence at ∼93 kya (95%CI:76-112 kya). We concur the earliest emerging L0d1'2 sublineage L0d1b (∼49 kya, 95%CI:37-58 kya) is widely distributed across southern Africa. Concomitantly, we find the most recent sublineage L0d2a (∼17 kya, 95%CI:10-27 kya) to be equally common. While we agree that lineages L0d1c and L0k1a are restricted to contemporary inland Khoesan populations, our observed predominance of L0d2a and L0d1a in non-Khoesan populations suggests a once independent coastal Khoesan prehistory. The distribution of early-diverged human maternal lineages within contemporary southern Africans suggests a rich history of human existence prior to any archaeological evidence of migration into the region. For the first time, we provide a genetic-based evidence for significant modern human evolution in southern Africa at the time of the Last Glacial Maximum at between ∼21-17 kya, coinciding with the emergence of major lineages L0d1a, L0d2b, L0d2d and L0d2a.

Somatic structural variants are an important contributor to cancer development and evolution. Accurate detection of these complex variants from whole genome sequencing data is influenced by a multitude of parameters. However, there are currently no tools for guiding study design nor are there applications that could predict the performance of somatic structural variant detection. To address this gap, we developed Shiny-SoSV, a user-friendly web-based calculator for determining the impact of common variables on the sensitivity, precision and F1 score of somatic structural variant detection, including choice of variant detection tool, sequencing depth of coverage, variant allele fraction, and variant breakpoint resolution. Using simulation studies, we determined singular and combinatoric effects of these variables, modelled the results using a generalised additive model, allowing structural variant detection performance to be predicted for any combination of predictors. Shiny-SoSV provides an interactive and visual platform for users to easily compare individual and combined impact of different parameters. It predicts the performance of a proposed study design, on somatic structural variant detection, prior to the commencement of benchwork. Shiny-SoSV is freely available at

Adaptation of global food systems to climate change is essential to feed the world. Tropical cattle production, a mainstay of profitability for farmers in the developing world, is dominated by heat, lack of water, poor quality feedstuffs, parasites, and tropical diseases. In these systems European cattle suffer significant stock loss, and the cross breeding of taurine x indicine cattle is unpredictable due to the dilution of adaptation to heat and tropical diseases. We explored the genetic architecture of ten traits of tropical cattle production using genome wide association studies of 4,662 animals varying from 0% to 100% indicine. We show that nine of the ten have genetic architectures that include genes of major effect, and in one case, a single location that accounted for more than 71% of the genetic variation. One genetic region in particular had effects on parasite resistance, yearling weight, body condition score, coat colour and penile sheath score. This region, extending 20 Mb on BTA5, appeared to be under genetic selection possibly through maintenance of haplotypes by breeders. We found that the amount of genetic variation and the genetic correlations between traits did not depend upon the degree of indicine content in the animals. Climate change is expected to expand some conditions of the tropics to more temperate environments, which may impact negatively on global livestock health and production. Our results point to several important genes that have large effects on adaptation that could be introduced into more temperate cattle without detrimental effects on productivity.

Creating a catalogue of early diverged genome variation is critical to determine the true extent of human diversity and associated medical impact. Generating deep whole genome data for 150 Khoe-San (12 groups, 1 unclassified), and 40 regionally comparative Southern Africans (3 groups), we identify ~30 million small-to-large variants - over 1.3 million unknown single nucleotide variants. Representing shared traditionally forager lifestyles and click-speaking languages, we identify San and Damara as separate phylogenetic lineages, contributing two admixture waves to Nama. While San represented modern humans’ deep divergence (~115 thousand years ago), Damara divergence is recent, with both showing high effective population sizes between 45–150 thousand years ago. Developing an assembly-based test we report 1,376 genes under positive selection ( dN / dS  = 19.46) of which 479 are significantly associated with forager peoples and, therefore, maintained ancestral alleles that differ from derived genetic variation observed in non-African biomedical resources. By generating whole genomes of 150 participants representing 12 Khoe-San click-speaking groups, the authors, reveal over 1.3 million unknown DNA variants, distinct San and here described Damara genetic trajectories, while achieving century-long global predominance.

Prostate cancer is characterized by considerable geo-ethnic disparity. African ancestry is a significant risk factor, with mortality rates across sub-Saharan Africa of 2.7-fold higher than global averages 1 . The contributing genetic and non-genetic factors, and associated mutational processes, are unknown 2 , 3 . Here, through whole-genome sequencing of treatment-naive prostate cancer samples from 183 ancestrally (African versus European) and globally distinct patients, we generate a large cancer genomics resource for sub-Saharan Africa, identifying around 2 million somatic variants. Significant African-ancestry-specific findings include an elevated tumour mutational burden, increased percentage of genome alteration, a greater number of predicted damaging mutations and a higher total of mutational signatures, and the driver genes  NCOA2 , STK19 , DDX11L1 , PCAT1  and  SETBP1 . Examining all somatic mutational types, we describe a molecular taxonomy for prostate cancer differentiated by ancestry and defined as global mutational subtypes (GMS). By further including Chinese Asian data, we confirm that GMS-B (copy-number gain) and GMS-D (mutationally noisy) are specific to African populations, GMS-A (mutationally quiet) is universal (all ethnicities) and the African–European-restricted subtype GMS-C (copy-number losses) predicts poor clinical outcomes. In addition to the clinical benefit of including individuals of African ancestry, our GMS subtypes reveal different evolutionary trajectories and mutational processes suggesting that both common genetic and environmental factors contribute to the disparity between ethnicities. Analogous to gene–environment interaction—defined here as a different effect of an environmental surrounding in people with different ancestries or vice versa—we anticipate that GMS subtypes act as a proxy for intrinsic and extrinsic mutational processes in cancers, promoting global inclusion in landmark studies. A molecular taxonomy for prostate cancer reveals a subtype associated with copy-number loss found in African and European populations that predicts poor outcomes and two subtypes—one associated with high mutational noise and one with copy-number gain—specific to African populations.

Background Congenital Muscular Torticollis (CMT) is the third most common musculoskeletal condition in infancy, and if untreated can lead to significant disability. While a range of conservative treatments are commonly used in the management of CMT, an understanding of their efficacy and safety is limited. This systematic review and meta-analysis, without language or discipline restriction, was conducted to address this knowledge gap. Methods Electronic searches of CENTRAL, PubMed, 22 other electronic databases, three trials registers and Google Scholar, were conducted for randomised controlled trials, which examined any non-surgical, non-pharmacological interventions, including but not limited to manual treatments, movement therapy, acupuncture, adjunctive therapies and physical support, in children aged 0 to 5 years with CMT. Two reviewers independently assessed the risk of bias of the included studies using the Cochrane Risk of bias 1 tool, rated their certainty of evidence using grading of recommendations assessment, development and evaluation (GRADE) framework, and performed random-effects meta-analyses. Results One hundred studies (80 from China) involving 8125 participants published between 1990 and 2023 were included. Adding manual therapy to an active control resulted in short-term improvements in passive cervical rotation (odds ratio (OR) 9.79, 95%CI 4.26,22.50), passive cervical lateroflexion (OR 2.66, 95%CI 1.17,6.04), active cervical rotation (OR 3.94, 95%CI 1.08,14.35), symmetric head posture (OR 4.55, 95%CI 2.57,8.05), sternocleidomastoid tumour thickness (mean difference (MD) -2.12 mm, 95%CI -2.98,-1.26) and development of symmetrical movement (standardised MD -0.70, 95%CI -0.95,-0.45). The addition of an electrophysical agent to an active control reduced sternocleidomastoid tumour thickness (MD -2.03 mm, 95%CI -2.67,-1.39) and optimised Tuina reduced tumour thickness more than traditional Tuina (MD -1.20 mm, 95%CI -1.80,-0.59). Adverse events were uncommon but poorly reported, with 71 (71%) of studies providing no data. Study heterogeneity limited pooling of data for meta-analysis, and there was very low to low certainty evidence for all results, due to high risk of bias, small sample sizes and study heterogeneity. Conclusions This review found that non-surgical, non-pharmacological treatments may be effective for CMT, but the certainty of evidence is very low to low. These findings are important in informing clinical guidelines and management for CMT and highlight an urgent need for large definitive trials that address the limitations of current studies. Protocol registration Cochrane Database of Systematic Reviews (No.: CD012987).