 above construct. In experiment 994 transformants were selected using the visual marker (GFP expression) and growth on herbicide, whilst on P5 media only. In experiment 9911 only selection on herbicide was used to select for transformation. Selection conditions in both experiments consisted of growth on P5 media containing 5 mg/l of the herbicide Basta (containing phosphinothricin) and 200 mg/l of timentin for 4–6 weeks with fortnightly subculture. Following this, cultures were transferred to P5 media plus 5 mg/l Basta for a further 4 weeks of culture. Cultures were then transferred to SM4 media for 6 weeks. In experiment 9911 the SM4 media included 5 mg/l Basta. Shoots from 9911 were rooted on 1/2MS30 plus 5 mg/l Basta. Shoots from experiment 994 were just rooted in 1/2MS30. Once vigorous root growth was established plants were transferred to the glasshouse.
Results
Putative transgenic plants were produced from both experiments 3 from 994 and 4 from 9911. Southern Blot analysis of clones of one transformant from each experiment demonstrated that the gfp gene was present in plants from both experiments and that both cultivars could be transformed (FIG. 5). When this blot was subsequently reprobed for the presence of the bar gene (FIG. 6) only the plants selected solely on the basis of the herbicide resistance were shown to contain the bar gene. These plants were then used for herbicide leaf paint assays and subsequ ntly sprayed with recommended field application rates of the herbicide Buster (active ingredient phosphinothricin). Control plants containing no bar gene showed noticeable wilt after 3 days and were essentially dead after 10 days following application of the herbicide, whilst the plants that contained the bar gene and had been selected on herbicide did not appear to be harmed and grew normally (FIG. 7).
Demonstration that Transformation is Independent of Cultivar, Construct, T-DNA and Selective Agent.
Further to examples 1–5, additional transgenic plants containing variations of the antisense alliinase construct (outlined in example 4) have been produced in additional cultivars CRON 12, CRON19 and CRON2. The nature of these plants has been confirmed by GFP expression where appropriate and regeneration on media containing geneticin. A summary of the plants produced in all the examples outlined above is given in table 3 to demonstrate the plasticity of the transformation system. In experiments that were not contaminated transgenic plants have been obtained from all cultivars so far tested.
We have developed a repeatable transformation system for onion. The regenerating primary transformants appear to be phenotypically normal. The GFP expression, as a visual selectable marker, enabled post transformation selection conditions to be optimised. The GFP marker has also proved useful in the selection of transgenic plants from other species that are difficult to transform (Vain et al. 1998). Selection conditions have now been established, which enable the identification of transformants solely on their ability to root in selective media (example 5).
This method of producing transgenic onions is repeatable and efficient. It takes a short time to produce transgenic plants and utilizes techniques have been shown to be cultivar independent (Example 6).
For example, this described process of transformation can be used with any species within the Allium and is not limited to onions. Work has shown that the described process of transformation is genotype independent.
It is to be understood that the scope of the invention is not limited to the described embodiments and therefore that numerous variations and modifications may be made to these embodiments without departing from the scope of the invention as set out in this specification.
The invention provides a novel method of transforming plants of the genus Allium and in particular onion plants. Also provided are plants transformed by the method. This allows Allium crop species which are an economically important vegetable species to be transformed by a variety of genes for improvement of Allium crop varieties.There appears to be a robust genetic link between body weight and major psychiatric disorders, an international research team has concluded.
Using data from more than a 500,000 individuals with major depression, bipolar disorder (BD), and schizophrenia, the investigators showed extensive genetic overlap between body mass index (BMI) and psychiatric disorders.
Interestingly, they found that although the genetic risk variants for major depression and BD were primarily associated with increased weight, the majority of genetic variants for schizophrenia were related to reduced weight.
"This difference in direction was quite interesting to us," principal investigator Ole A. Andreassen, MD, PhD, told Medscape Medical News. "Most of the gene variants overlapping between BMI and depression/bipolar disorder were in the same direction and were associated with higher BMI.
"So if you had a susceptibility for increased BMI, you were also likely to suffer from depression or bipolar disorder," said Andreassen, who is professor of medicine at the University of Oslo, in Norway. "But for schizophrenia, it was the opposite direction: if you were at risk of schizophrenia, you were less likely to be obese."
The study was published online January 8 in JAMA Psychiatry.
For individuals who suffer major psychiatric disorders, life spans are cut short by 10 to 20 years compared to the general population. This difference, the investigators note, is primarily due to high rates of cardiometabolic risk factors, such as obesity, that are significant contributors to comorbid cardiovascular disease.
Although both behavioral/lifestyle factors and psychopharmacologic medications have significant adverse metabolic effects, the polygenic nature of major psychiatric disorders is becoming increasingly clear. Indeed, the heritability of both obesity and major psychiatric disorders is substantial.
What's more, previous genome-wide association studies (GWAS) have identified common variants involved in BMI and schizophrenia, BD, and major depression. Nevertheless, there are still relatively few data regarding genetic variants that jointly influence both major psychiatric disorders and BMI.
"People with bipolar disorder and major depression seem to have a genetic risk for increased body mass which, together with diet, lifestyle, and medication, can explain the increased weight that many patients experience," the study's first authors, Shahram Bahrami, PhD, and Nils Eiel Steen, MD, PhD, said in a statement.
"There is also this scientific question about how our mental function and physical body interact," said Andreassen.
To help answer these questions, the researchers assessed the extent of overlap between the genetic architectures of major psychiatric disorders and BMI by identifying potential shared genetic loci.
The investigators used a conditional false discovery rate statistical framework to analyze independent GWAS data on 1,380,284 individuals from large study cohorts around the world. These included 82,315 individuals with schizophrenia, 51,710 with bipolar disorder, and 480,359 with major depression.
An additional 795,640 patients with obesity, as determined by BMI, were also included. The data were collected between August 2017 and May 2018, and the analysis began in July 2018.
The study's primary outcome was a list of genetic loci shared with obesity, as determined by BMI, and major psychiatric disorders, as well as their functional pathways.
FUMA, a Web-based platform that facilitates functional annotation of GWAS results, was used to define the independent genomic loci. Advanced statistical methods were used to examine and compare the genetic variants involved in increased body weight and severe mental disorders.
Perhaps not surprisingly, the study showed that the genetic correlation between BMI obesity and major psychiatric disorders varied significantly (schizophrenia: r for genetic = –0.11; P = 2.1×10-10; bipolar disorder: r for genetic = –0.06; P =.0103; major depression: r for genetic = 0.12; P = 6.7×10-10).
Nevertheless, the investigation also revealed extensive genetic overlap between BMI and psychiatric disorders. There were 63 shared loci for obesity and schizophrenia, 17 for obesity and BD, and 32 for obesity and major depression, at a conjunctional false discovery rate <0.01.
Of the shared loci, 34% (73 of 213) in schizophrenia had risk alleles that were associated with higher BMI (conjunctional false discovery rate, <0.05). In comparison, 52% of shared loci (36 of 69) in BDE had risk alleles associated with higher BMI, as did 57% (56 of 99) in major depression (conjunctional false discovery rate, <0.05). The rest of the shared loci had opposite directions of associations.
Functional analyses of these associations indicated that the overlapping loci are involved in several pathways, including neurodevelopment, neurotransmitter signaling, and intracellular processes. On the other hand, loci with concordant and opposite association directions pointed mostly to different pathways.
Although these findings suggest shared molecular mechanisms between weight regulation and mental illness, there was also a striking difference between disorders.
Although the genetic risk variants for major depression and BD were primarily associated with increased weight, most of the genetic variants in schizophrenia were related to reduced weight.
"So to me, what we can conclude from the study is that increased body weight in schizophrenia seems to be directed mainly by diet, lifestyle, and side effects of medication, but it's a completely different picture with bipolar disorder and depression,” said Andreassen.
Doorway to Personalized Treatment?
Commenting on the findings for Medscape Medical News, Cynthia Bulik, PhD, distinguished professor of psychiatry, University of North Carolina at Chapel Hill, said she was not particularly surprised by the findings.
"One thing genomic research is teaching us is the dividing line of above the neck [for psychiatric traits] and below the neck [for cardiometabolic traits] is indeed arbitrary," said Bulik, who was not involved in the study.
"Aligned with epidemiological findings, these results underscore the importance of considering both metabolic and psychiatric factors when trying to understand and treat mental illness effectively.
"These results also unders