Predicting whether and how populations will adapt to rapid climate change is a critical goal for evolutionary biology. To examine the genetic basis of fitness and predict adaptive evolution in novel climates with seasonal variation, we grew a diverse panel of the annual plant Arabidopsis thaliana (multiparent advanced generation intercross lines) in controlled conditions simulating four climates: a present-day reference climate, an increased-temperature climate, a winter-warming only climate, and a poleward-migration climate with increased photoperiod amplitude. In each climate, four successive seasonal cohorts experienced dynamic daily temperature and photoperiod variation over a year. We measured 12 traits and developed a genomic prediction model for fitness evolution in each seasonal environment. This model was used to simulate evolutionary trajectories of the base population over 50 y in each climate, as well as 100-y scenarios of gradual climate change following adaptation to a reference climate. Patterns of plastic and evolutionary fitness response varied across seasons and climates. The increased-temperature climate promoted genetic divergence of subpopulations across seasons, whereas in the winter-warming and poleward-migration climates, seasonal genetic differentiation was reduced. In silico "resurrection experiments" showed limited evolutionary rescue compared with the plastic response of fitness to seasonal climate change. The genetic basis of adaptation and, consequently, the dynamics of evolutionary change differed qualitatively among scenarios. Populations with fewer founding genotypes and populations with genetic diversity reduced by prior selection adapted less well to novel conditions, demonstrating that adaptation to rapid climate change requires the maintenance of sufficient standing variation.climate change | annual plant | genomic prediction | season O ngoing climate change is causing rapid shifts in environmental selective pressures within local populations (1, 2). To persist, populations must track the shifting multivariate trait optimum by phenotypic plasticity or adaptive evolution (3, 4), or migrate to keep up with poleward shifts in their original climate niche (1). The outcome of these responses to climate change will depend upon the seasonal variation a population experiences, particularly in temperate climates, where seasonality is a major source of environmental heterogeneity (5, 6). Understanding adaptation to seasonal environments is critical for predicting the response to climate change in short-lived organisms with multiple generations per year, like many insects and annual plants. Such prediction requires theoretical projections based on solid empirical foundations, tracking phenotypic change in complex traits as well as in the molecular variation present within populations as they adapt to different seasons. Here, we use a genomic prediction model, based on experimental data from Arabidopsis thaliana, to simulate trajectories of adaptation to novel climate scenarios in season...

Major alleles for seed dormancy and flowering time are well studied, and can interact to influence seasonal timing and fitness within generations. However, little is known about how this interaction controls phenology, life history, and population fitness across multiple generations in natural seasonal environments. To examine how seed dormancy and flowering time shape annual plant life cycles over multiple generations, we established naturally dispersing populations of recombinant inbred lines of Arabidopsis thaliana segregating early and late alleles for seed dormancy and flowering time in a field experiment. We recorded seasonal phenology and fitness of each genotype over 2 yr and several generations. Strong seed dormancy suppressed mid-summer germination in both early- and late-flowering genetic backgrounds. Strong dormancy and late-flowering genotypes were both necessary to confer a winter annual life history; other genotypes were rapid-cycling. Strong dormancy increased within-season fecundity in an early-flowering background, but decreased it in a late-flowering background. However, there were no detectable differences among genotypes in population growth rates. Seasonal phenology, life history, and cohort fitness over multiple generations depend strongly upon interacting genetic variation for dormancy and flowering. However, similar population growth rates across generations suggest that different life cycle genotypes can coexist in natural populations.

Background Colonization increases risk for invasive candidiasis in neonates. Breast milk host defense proteins may affect yeast colonization of infants. Objective To evaluate breast milk host-defense proteins relative to yeast colonization in infants. Methods Infants admitted for longer than 72h to the NICU at Women and Infants Hospital in Providence, RI, were eligible. After consent, expressed breast milk and swabs from oral, rectal, and inguinal sites from infants were cultured weekly for 12 weeks, or until discharge, transfer, or death. Breast milk was tested for levels of human lactoferrin, lysozyme, apolipoprotein J, mucin-1, dermcidin, and soluble CD14 using commercial ELISA. Concentrations of these components were compared in breast milk received by infants who were colonized or not colonized with yeast. Results From an original cohort of 130, 61 infants had samples available for this subanalysis. A convenience sample of stored breast milk was analyzed. Median lactoferrin, apolipoprotein J, and mucin-1, did not differ between colonized and uncolonized groups. Soluble CD14 was higher in the surface-colonized group (1.8 μg/ml, n=12) compared with the surface-uncolonized group (1.6 μg/ml, n=12, p=0.02). Median lysozyme levels were higher in the surface-uncolonized group (483.0 ng/ml, n=12) vs. the surface-colonized group (298.3 ng/ml, n=12, p=0.04). Median dermcidin levels were higher in the surface-uncolonized group (19.4 ng/ml, n= 12) vs. the surface-colonized group (8.7 ng/ml, n=12, p=0.04). Conclusions This study shows an association between colonization with Candida in neonates and lower levels lysozyme and dermcidin in received breast milk. Further study is needed to confirm these findings.

Recovery of yeast from breast milk is associated with colonization with yeast in the neonate. Because Candida transmission via breast milk had a 30% concordance, breast milk is only one of several ways colonization occurs. Further study is needed on mechanisms of colonization.