Can you make morphometrics work when you know the right answer? Pick and mix approaches for apple identification

Morphological classification of living things has challenged science for several centuries and has led to a wide range of objective morphometric approaches in data gathering and analysis. In this paper we explore those methods using apple cultivars, a model biological system in which discrete groups are pre-defined but in which there is a high level of overall morphological similarity. The effectiveness of morphometric techniques in discovering the groups is evaluated using statistical learning tools. No one technique proved optimal in classification on every occasion, linear morphometric techniques slightly out-performing geometric (72.6% accuracy on test set versus 66.7%). The combined use of these techniques with post-hoc knowledge of their individual successes with particular cultivars achieves a notably higher classification accuracy (77.8%). From this we conclude that even with pre-determined discrete categories, a range of approaches is needed where those categories are intrinsically similar to each other, and we raise the question of whether in studies where potentially continuous natural variation is being categorised the level of match between categories is routinely set too high

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders

Harvesting fruit of equivalent chronological age and fruit position shows individual effects of UV radiation on aspects of the strawberry ripening process

The effect of UV radiation on fruit secondary compounds of strawberry cv ‘Elsanta’ was recorded taking chronological age and fruit position on the truss into account. When fruit of similar age post-anthesis, and truss position were compared, we found that the concentration of secondary compounds differed according to fruit position on the truss. UV radiation hastened the rate of colour development and resulted in an increase in fruit anthocyanin (14–31%), flavonoid (9–21%) and phenolic (9–20%) contents at harvesting; but it had no effect on fruit soluble solid content, pH and volatile composition. It did, however, increase leaf flavonoid (16%) and phenolic (8%) concentrations. Fruit ripened under a UV transparent film were firmer, smaller but greater in number than fruit ripened under a UV opaque film. Overall, the results indicate that UV radiation does not affect all aspects of strawberry ripening but independently alters rate of colour development and fruit firmnes

Leafy, terminal flower1 and agamous are functionally conserved but do not regulate terminal flowering and floral determinacy in Impatiens balsamina

In Impatiens balsamina a lack of commitment of the meristem during floral development leads to the continuous requirement for a leaf-derived floral signal. In the absence of this signal the meristem reverts to leaf production. Current models for Arabidopsis state that LEAFY (LFY) is central to the integration of floral signals and regulates flowering partly via interactions with TERMINAL FLOWER1 (TFL1) and AGAMOUS (AG). Here we describe Impatiens homologues of LFY, TFL1 and AG (IbLFY, IbTFL1 and IbAG) that are highly conserved at a sequence level and demonstrate homologous functions when expressed ectopically in transgenic Arabidopsis. We relate the expression patterns of IbTFL1 and IbAG to the control of terminal flowering and floral determinacy in Impatiens. IbTFL1 is involved in controlling the phase of the axillary meristems and is expressed in axillary shoots and axillary meristems which produce inflorescences, but not in axillary flowers. It is not involved in maintaining the terminal meristem in either an inflorescence or indeterminate state. Terminal flowering in Impatiens appears therefore to be controlled by a pathway that uses a different integration system than that regulating the development of axillary flowers and branches. The pattern of ovule production in Impatiens requires the meristem to be maintained after the production of carpels. Consistent with this morphological feature IbAG appears to specify stamen and carpel identity, but is not sufficient to specify meristem determinacy in Impatiens

Analysis of Shared Heritability in Common Disorders of the Brain

Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology