Genome-wide shifts in climate-related variation underpin responses to selective breeding in a widespread conifer

Locally adapted temperate tree populations exhibit genetic trade-offs among climate-related traits that can be exacerbated by selective breeding and are challenging to manage under climate change. To inform climatically adaptive forest management, we investigated the genetic architecture and impacts of selective breeding on four climate-related traits in 105 natural and 20 selectively bred lodgepole pine populations from western Canada. Growth, cold injury, growth initiation, and growth cessation phenotypes were tested for associations with 18,600 single-nucleotide polymorphisms (SNPs) in natural populations to identify “positive effect alleles” (PEAs). The effects of artificial selection for faster growth on the frequency of PEAs associated with each trait were quantified in breeding populations from different climates. Substantial shifts in PEA proportions and frequencies were observed across many loci after two generations of selective breeding for height, and responses of phenology-associated PEAs differed strongly among climatic regions. Extensive genetic overlap was evident among traits. Alleles most strongly associated with greater height were often associated with greater cold injury and delayed phenology, although it is unclear whether potential trade-offs arose directly from pleiotropy or indirectly via genetic linkage. Modest variation in multilocus PEA frequencies among populations was associated with large phenotypic differences and strong climatic gradients, providing support for assisted gene flow polices. Relationships among genotypes, phenotypes, and climate in natural populations were maintained or strengthened by selective breeding. However, future adaptive phenotypes and assisted gene flow may be compromised if selective breeding further increases the PEA frequencies of SNPs involved in adaptive trade-offs among climate-related traits.

Local adaptation of climate-related traits in widespread temperate conifers has been demonstrated for centuries using extensive long-term common garden experiments (1, 2). As early as the 17th century, foresters were instructed to recognize variation in desirable traits and select seed from trees with favorable phenotypes (3). Modern tree improvement programs systematically select upon genetic variation, primarily to achieve growth gains and meet economic objectives. Estimates of genetic variation and gains from selection made using quantitative genetic models assume many anonymous loci of small effect underlie both variation in continuously distributed phenotypes and their responses to selective breeding. However, the type, quantity, effect size, distribution, and dynamics of genes underlying locally adaptive phenotypic variation and responses to selective breeding in forest trees are still poorly understood (4).Directional selection over hundreds or thousands of generations has led to genomic features of domestication in agricultural crops including simplified genetic architectures underlying many traits, reduced genome-wide diversity, and numerous selective sweeps (5–7). Beyond high-gain, short-rotation clonal forestry [e.g., Eucalyptus spp. (8)], we know little about the effects of artificial selection on adaptive genetic variation in forest trees, yet many tree species undergo some degree of selective breeding. Two or three generations of conifer breeding is not expected to have the same magnitude of genetic effects seen in domesticated crops, but if artificial selection for increased productivity is detectable in conifer genomes, it may expose genetic relationships and potential sources of trade-offs between growth and climatically adaptive phenotypes.Climate-related adaptive traits are often intercorrelated due to pleiotropy, natural selection, or linkage disequilibrium (LD), so that strong directional selection on one trait can cause correlated responses in others. Pleiotropic allelic variants associated with phenotypes do not function in isolation. Antagonistic pleiotropic effects among traits can generate adaptive trade-offs among traits within populations, and limit gains from selection on a focal trait (9). Trait–trait correlations can also arise through strong selection acting in parallel on unlinked loci or from LD mediated by physical linkage of loci on chromosomes. Average genome-wide LD estimates in conifers appear to be low (10, 11) but may be greater (r² of 0.2–0.4) within genes under strong selection (12).Conifer studies have identified putatively adaptive phenotype-associated alleles on a locus-by-locus basis using quantitative trait loci (QTL) mapping or genotype–phenotype associations (GPAs) (also known as genome-wide association studies [GWAS]) (13). Genotype–environment association analyses in conifers have identified putatively adaptive environmentally associated loci (e.g., 14, 15), but loci are usually anonymous relative to adaptive phenotypes. All of these approaches are biased toward detecting loci with large phenotypic effects, but expectations that genome scans will discover individual adaptive loci with large effects or frequency differences among populations may be biologically and statistically unrealistic (16, 17). Conifer GPA studies typically detect relatively few statistically significant loci, and locus-by-locus analyses are insufficient to characterize adaptive genome-wide variation associated with adaptive traits and signatures of selective breeding. Multilocus tests for adaptive polygenic signatures of selection have been developed (e.g., refs. 18 and 19), but significant limitations remain (reviewed in refs. 20 and 21).Uncertainty about the effects of selective breeding on adaptive genetic variation is layered upon expectations that forest trees will become maladapted as climates shift (22). Efforts are being made to estimate maladaptation using genome-wide variation associated with adaptive traits and climate (23, 24), because conserving, managing, and efficiently redeploying genetic variation associated with adaptive phenotypes will be a necessary element of strategies to mitigate the effects of shifting climates on forest resources (25). Assisted gene flow strategies in temperate and subboreal forests generally aim to move trees to cooler climates in anticipation of future warming, but trees must then contend with the increased short- to medium-term risk of maladaptation to damaging frost. This means cold tolerance is, perhaps surprisingly, an important trait when planning for warming climates.Genetic approaches have the potential to efficiently and accurately characterize local adaptation to climate. Understanding whether this potential can be realized in a technically robust and operationally feasible way, and whether selection for faster growth compromises genetic variation associated with phenotypic adaptation to climate, has far-reaching implications for developing effective assisted gene flow strategies that mitigate negative climate change impacts on forest health and timber production (26, 27). In this context, our research objectives are to 1) identify the genetic architecture of climate-related adaptive traits in interior lodgepole pine (Pinus contorta Dougl. ex Loud. var. latifolia Engelm.); 2) identify genome-wide effects of artificial selection for increased productivity on climate-related traits; and 3) assess the implications of genetic responses to selection for assisted gene flow strategies.Our study combines climatic data, genotype data from ∼50,000 lodgepole pine single-nucleotide polymorphisms (SNPs), and seedling phenotypic data for height, cold injury, growth initiation, and growth cessation traits. These data were collected from a seedling common garden that sampled reforestation seed lots from 105 natural populations and 20 breeding populations from across the species’ range in Alberta (AB) and British Columbia (BC), Canada (Fig. 1 and SI Appendix, Table S1). For each of the four traits, we identify range-wide GPAs using 929 seedlings from all 105 natural populations. Then for the 1% most strongly phenotype-associated SNPs, we examine how artificial selection within breeding populations has changed allele frequencies at individual SNP loci, within individual seedlings, populations (breeding zones), and three climatic regions (Fig. 1). Using elements from the approach of Turchin et al. (18), we study changes in frequency of the alleles that have a positive effect on adaptive traits (positive effect alleles [PEAs]). At each SNP locus, a PEA is the allele associated with increasing numeric values of the respective phenotype, determined in this case through GPA analyses in the natural seedling populations. PEAs reported here are associated with greater seedling height, greater cold injury, delayed growth initiation, and delayed growth cessation. To parse physical genetic linkage from allelic associations due to other causes, we compare LD estimated from our natural seedlings with estimates of recombination among haploid megagametophytes from a single maternal parent, where physical linkage is the only cause of LD. Integrating genetic, climatic, and phenotypic data gives us a robust basis to detect the effects of artificial selection on climate-related genotypes that are relevant to breeding and assisted gene flow strategies.Open in a separate windowFig. 1.Geographic origins of the natural and selected seedling populations sampled from across the range of lodgepole pine in Alberta (AB) and British Columbia (BC). Natural populations are represented by filled circles; selected seedling breeding zones are represented by filled polygons. The three climatic regions we used were AB, BC-Central, and BC-South. AB breeding zones are formally identified as A, B1, B2, C, J, and K1. BC-Central breeding zone abbreviations are as follows: BV, Bulkley Valley; CP, Central Plateau; and PG, Prince George. BC-South breeding zone abbreviations are as follows: EK, East Kootenay; NE, Nelson; and TO, Thompson–Okanagan. Reprinted from ref. 35, with permission from Elsevier.     

In vitro production of panton-valentine leukocidin among strains of methicillin-resistant Staphylococcus aureus causing diverse infections.

BACKGROUND: Community-acquired methicillin-resistant Staphylococcus aureus strains have recently been associated with severe necrotizing infections. Greater than 75% of these strains carry the genes for Panton-Valentine leukocidin (PVL), suggesting that this toxin may mediate these severe infections. However, to date, studies have not provided evidence of toxin production. METHODS: Twenty-nine community-acquired methicillin-resistant Staphylococcus aureus and 2 community-acquired methicillin-susceptible S. aureus strains were collected from patients with infections of varying severity. Strains were analyzed for the presence of lukF-PV and SCCmecA type. PVL production in lukF-PV gene-positive strains was measured by ELISA, and the amount produced was analyzed relative to severity of infection. RESULTS: Only 2 of the 31 strains tested, 1 methicillin-resistant Staphylococcus aureus abscess isolate and 1 nasal carriage methicillin-susceptible S. aureus isolate, were lukF-PV negative. All methicillin-resistant Staphylococcus aureus strains were SCCmec type IV. PVL was produced by all strains harboring lukF-PV, although a marked strain-to-strain variation was observed. Twenty-six (90%) of 29 strains produced 50-350 ng/mL of PVL; the remaining strains produced PVL in excess of 500 ng/mL. The quantity of PVL produced in vitro did not correlate with severity of infection. CONCLUSIONS: Although PVL likely plays an important role in the pathogenesis of these infections, its mere presence is not solely responsible for the increased severity. Factors that up-regulate toxin synthesis in vivo could contribute to more-severe disease and worse outcomes in patients with community-acquired methicillin-resistant Staphylococcus aureus infection.     

Metabolic syndrome in Zambian adults with human immunodeficiency virus on antiretroviral therapy: Prevalence and associated factors

Metabolic syndrome (MetS) is a constellation of factors including hypertension, abdominal obesity, dyslipidemia, and insulin resistance that separately and together significantly increase risk for cardiovascular disease (CVD) and diabetes. In sub-Saharan Africa, with a substantial burden of human immunodeficiency virus (HIV) and increasing prevalence of CVD and diabetes, there is a paucity of epidemiological data on demographic, laboratory, and clinical characteristics associated with MetS among people with HIV (people with human [PWH]). Therefore, this study aimed to determine the burden and factors influencing MetS in antiretroviral therapy (ART)-experienced individuals in Zambia.We collected cross-sectional demographic, lifestyle, anthropometric, clinical, and laboratory data in a cohort of ART-experienced (on ART for ≥6 months) adults in 24 urban HIV treatment clinics of Zambia between August, 2016 and May, 2020. MetS was defined as having ≥3 of the following characteristics: low high density lipoprotein cholesterol (HDL-c) (<1.0 mmol/L for men, <1.3 for women), elevated waist circumference (≥94 cm for men, ≥80 cm for women), elevated triglycerides (≥1.7 mmol/L), elevated fasting blood glucose (≥5.6 mmol/L), and elevated blood pressure (BP) (systolic BP ≥130 or diastolic BP ≥85 mm Hg). Virological failure (VF) was defined as HIV viral load ≥1000 copies/mL. The following statistical methods were used: Chi-square test, Wilcoxon rank-sum test, and multivariable logistic regression.Among 1108 participants, the median age (interquartile range [IQR]) was 41 years (34, 49); 666 (60.1%) were females. The prevalence of MetS was 26.3% (95% confidence interval [CI] 23.9–29.1). Age (adjusted odds ratio [OR] 1.07; 95% CI 1.04–1.11), female sex (OR 3.02; 95% CI 1.55–5.91), VF (OR 1.98; 95% CI 1.01–3.87), dolutegravir (DTG)-based regimen (OR 2.10; 95% CI 1.05–4.20), hip-circumference (OR 1.03; 95% CI 1.01–1.05), T-lymphocyte count (OR 2.23; 95% CI 1.44–3.43), high-sensitivity C-reactive protein (hsCRP) (OR 1.14; 95% CI 1.01–1.29), and fasting insulin (OR 1.02; 95% CI 1.01–1.04) were significantly associated with MetS.Metabolic syndrome was highly prevalent among HIV+ adults receiving ART in Zambia and associated with demographic, clinical, anthropometric, and inflammatory characteristics. The association between MetS and dolutegravir requires further investigation, as does elucidation of the impact of MetS on ART outcomes in sub-Saharan African PWH.     

Blocking protein farnesyltransferase improves nuclear blebbing in mouse fibroblasts with a targeted Hutchinson-Gilford progeria syndrome mutation

Hutchinson-Gilford progeria syndrome (HGPS), a progeroid syndrome in children, is caused by mutations in LMNA (the gene for prelamin A and lamin C) that result in the deletion of 50 aa within prelamin A. In normal cells, prelamin A is a "CAAX protein" that is farnesylated and then processed further to generate mature lamin A, which is a structural protein of the nuclear lamina. The mutant prelamin A in HGPS, which is commonly called progerin, retains the CAAX motif that triggers farnesylation, but the 50-aa deletion prevents the subsequent processing to mature lamin A. The presence of progerin adversely affects the integrity of the nuclear lamina, resulting in misshapen nuclei and nuclear blebs. We hypothesized that interfering with protein farnesylation would block the targeting of progerin to the nuclear envelope, and we further hypothesized that the mislocalization of progerin away from the nuclear envelope would improve the nuclear blebbing phenotype. To approach this hypothesis, we created a gene-targeted mouse model of HGPS, generated genetically identical primary mouse embryonic fibroblasts, and we then examined the effect of a farnesyltransferase inhibitor on nuclear blebbing. The farnesyltransferase inhibitor mislocalized progerin away from the nuclear envelope to the nucleoplasm, as determined by immunofluoresence microscopy, and resulted in a striking improvement in nuclear blebbing (P < 0.0001 by chi2 statistic). These studies suggest a possible treatment strategy for HGPS.     

System for Rapid Assessment of Pneumonia and Influenza-Related Mortality—Ohio, 2009–2010

Rapid mortality surveillance is critical for state emergency preparedness. To enhance timeliness during the 2009–2010 influenza A H1N1 pandemic, the Ohio Department of Health activated a drop-down menu within Ohio’s Electronic Death Registration System for reporting of pneumonia- or influenza-related deaths approximately 5 days postmortem. We used International Classification of Diseases—Tenth Revision (ICD-10) codes, available 2–3 months postmortem as the standard, and assessed their agreement with drop-down-menu codes for pneumonia- or influenza-related deaths. Among 56 660 Ohio deaths during September 2009–March 2010, agreement was 97.9% for pneumonia (κ = 0.85) and 99.9% for influenza (κ = 0.79). Sensitivity was 80.2% for pneumonia and 73.9% for influenza. Drop-down menu coding enhanced timeliness while maintaining high agreement with ICD-10 codes.     

Vital Signs: Estimated Effects of a Coordinated Approach for Action to Reduce Antibiotic-Resistant Infections in Health Care Facilities — United States

BackgroundTreatments for health care–associated infections (HAIs) caused by antibiotic-resistant bacteria and Clostridium difficile are limited, and some patients have developed untreatable infections. Evidence-supported interventions are available, but coordinated approaches to interrupt the spread of HAIs could have a greater impact on reversing the increasing incidence of these infections than independent facility-based program efforts.MethodsData from CDC’s National Healthcare Safety Network and Emerging Infections Program were analyzed to project the number of health care–associated infections from antibiotic-resistant bacteria or C. difficile both with and without a large scale national intervention that would include interrupting transmission and improved antibiotic stewardship. As an example, the impact of reducing transmission of one antibiotic-resistant infection (carbapenem-resistant Enterobacteriaceae [CRE]) on cumulative prevalence and number of HAI transmission events within interconnected groups of health care facilities was modeled using two distinct approaches, a large scale and a smaller scale health care network.ResultsImmediate nationwide infection control and antibiotic stewardship interventions, over 5 years, could avert an estimated 619,000 HAIs resulting from CRE, multidrug-resistant Pseudomonas aeruginosa, invasive methicillin-resistant Staphylococcus aureus (MRSA), or C. difficile. Compared with independent efforts, a coordinated response to prevent CRE spread across a group of inter-connected health care facilities resulted in a cumulative 74% reduction in acquisitions over 5 years in a 10-facility network model, and 55% reduction over 15 years in a 102-facility network model.ConclusionsWith effective action now, more than half a million antibiotic-resistant health care–associated infections could be prevented over 5 years. Models representing both large and small groups of interconnected health care facilities illustrate that a coordinated approach to interrupting transmission is more effective than historical independent facility-based efforts.Implications for Public HealthPublic health–led coordinated prevention approaches have the potential to more completely address the emergence and dissemination of these antibiotic-resistant organisms and C. difficile than independent facility–based efforts.