NEW YORK (GenomeWeb News) – A genome sequencing study of the Chinese alligator Alligator sinensis, appearing in Cell Research, is providing genetic hints about the endangered crocodilian's biology and evolutionary history.
Researchers from Zhejiang University and BGI-Shenzhen sequenced a Chinese alligator sample from a nature reserve in China's Zhejiang Province, generating a genome sequence that's roughly 2.3 billion bases long. The group's analysis revealed that almost 40 percent of the genome is made up of repeat sequence, though it also contains an estimated 22,200 protein-coding genes.
Among genes showing signs of positive selection in the genome, the team found genes suspected of contributing to the Chinese alligator's sensory skills — such as vision/night vision, nerve, and scent perception genes — and its top-notch breath-holding habits. The new genome also offered hints about the advent of temperature-dependent sex determination in the Chinese alligator, which does not have sex chromosomes.
Bipolar disorder, major depressive disorder and schizophrenia seem to share more common genetic risk factors with one another than with autism spectrum disorder or attention-deficit/hyperactivity disorder, according to a genome-wide association analysis published in Nature Genetics.
Members of the Psychiatric Genomics Consortium's cross-disorder group used a statistical modeling method to assess genotyping data for tens of thousands of cases and control sampled from across the five conditions.
Their results suggest that the overlap between genetic risk factors for schizophrenia and bipolar disorder is most pronounced. Major depressive disorder appears to share a moderate number of risk variants with schizophrenia, with bipolar disorder, and with ADHD. On the other hand, researchers reported, schizophrenia and ASD shared a relatively low proportion of their risk variants, while other pairs of conditions did not show discernible genetic overlap with one other.
"These results give us by far the clearest picture available to date of the degree of genetic similarity between these key psychiatric disorders," co-senior author Kenneth Kendler, a human and molecular genetics and psychiatry researcher at Virginia Commonwealth University, said in a statement.
"We hope that this will help us both in developing a more scientifically based diagnostic system," he said, "and understanding the degree of sharing of the biological foundation these illnesses."
Members of another large team, led by researchers at the University of Colorado and the University of Queensland, focused their attention on schizophrenia risk variants that may or may not be shared between individuals of European or African descent — work that they described in the American Journal of Human Genetics.
Using a computational approach called bivariate linear mixed-effects modeling, the group looked at how well additive SNP effects could explain inherited schizophrenia risk in African-American populations and considered the extent to which schizophrenia risk alleles in that population coincide with those described in individuals with European ancestry.
Based on autosomal SNP data for more than 7,000 African-American or European individuals with schizophrenia and almost 6,800 ancestry-matched controls assessed through past GWAS by the Molecular Genetics of Schizophrenia Collaboration, the researchers concluded that their statistical strategy could be used to quantify shared genetic risk for schizophrenia between the populations — an analysis that they extended to include nearly 6,700 more European cases and controls from the International Schizophrenia Consortium.
For the common SNPs considered, the additive genetic variation associated with schizophrenia risk appears to be largely shared between African-American populations and populations with European ancestry, the study's authors reported, hinting that some of these schizophrenia risk variants may have been present prior to splits between human populations.
Still, they cautioned that "[b]ecause SNPs included in GWASs are unlikely to tag the effects of rare causal variants and because rarer causal variants are increasingly likely to be population specific, these estimates are unlikely to apply to the portion of schizophrenia heritability caused by rare causal variants."
In a study slated to appear online in the Journal of Clinical Investigation, a team from the US and Japan highlighted a protein expression signature that appears to show promise for predicting ovarian cancer recurrence after platinum-based chemotherapy.
Starting from more than 400 serous epithelial ovarian cancer samples collected as part of the Cancer Genome Atlas study, the researchers narrowed in on samples for which progression-free survival data was available. They then relied on reverse-phase protein arrays to profile protein patterns in these fresh frozen resected tumor samples, collected from women with serous ovarian cancer before chemotherapy.
With that data, they narrowed in on nine protein markers whose expression appeared to correspond to patient outcomes. In a set of 226 more ovarian cancer samples, this protein expression-based classification scheme — dubbed "Protein-driven index of Ovarian cancer," or PROVAR — accurately distinguished ovarian cancer patients who were at high risk of recurrence from those who weren't. And in data from 387 ovarian cancer samples from TCGA, the signature appeared to correctly classify cases based on overall survival patterns as well.
"Integrating the protein signature with genetic mutations associated with survival will likely result in the most optimal predictive model of outcome," University of Texas MD Anderson Cancer Center researcher Roel Verhaak, the study's corresponding author, and colleagues noted.
"In the era of personalized medicine," they concluded, "identification of patients at high risk of early recurrence may provide clinicians with opportunities for early interference and positively impact survival for a group of patients in dire need of improved prospects."