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Science Studies Present Method to Visualize 3D Genome Structure, RNAi Screens to Study Insect Horns

Stanford University's Longzhi Tan has been awarded the 2019 Science & SciLifeLab Prize for Young Scientists grand prize for developing a method to visualize the three-dimensional genome structures of single cells. Studying 3D structures in the human genome is complicated by the cells' diploid nature. "The 23 chromosomes inherited from one's mother and the 23 from one's father differ by less than .1 percent, making it difficult to distinguish the parent of origin for each observed contact," Tan writes in Science. To overcome this challenge, he developed an algorithm that aggregates the minute parental differences from many neighboring contacts to accurately infer their common parent of origin. "With these biochemical and computational advances — together termed diploid chromosome conformation capture (Dip-C) — we can now look at almost any cell in the human body."

Using a series of RNA interference knockdown screens, a team of Indiana University scientists show that beetle horns and insect wings share genetic origins. In a study appearing in Science, the investigators examined the origin of prothoracic horns — one of the most pronounced examples of secondary sexual traits among animals — in three species of dung beetles that reflect a range of horn formation diversity. In light of earlier research suggesting that non-wing-bearing thoracic segments contain wing serial homologs that may have been co-opted to evolve other structures, the study's authors used RNAi to suppress genes related to wing development to see if there was any effect on horn growth. They find that the prothoracic horns of beetles derive partly from wing serial homologs, and suggest that "other insect innovations may derive similarly from wing serial homologs and the concomitant establishment of structure-specific transcriptional landscapes."

By performing RNA sequencing on skin lesions associated with infection by the parasite Leishmania braziliensis, an international research team has identified gene expression patterns that may help predict which patients will respond to treatment. The parasitic infection is widespread in the developing world and causes skin lesions that sometimes become malignant. While pentavalent antimonials can treat the infection, they are often ineffective. As reported in Science Translational Medicine, the scientists sequenced patient samples to identify variably expressed genes that correlate with treatment outcomes, including ones involved in cytolysis. Additionally, they find that lesions from patients who did not respond to treatment have a higher parasite load. Using a host-pathogen marker profile of as few as three genes, the team was able to predict patient outcomes before the initiation of treatment, which may help in the development of a point-of-care diagnostic for precision treatment of the disease.

The Scan

Machine Learning Helps ID Molecular Mechanisms of Pancreatic Islet Beta Cell Subtypes in Type 2 Diabetes

The approach helps overcome limitations of previous studies that had investigated the molecular mechanisms of pancreatic islet beta cells, the authors write in their Nature Genetics paper.

Culture-Based Methods, Shotgun Sequencing Reveal Transmission of Bifidobacterium Strains From Mothers to Infants

In a Nature Communications study, culture-based approaches along with shotgun sequencing give a better picture of the microbial strains transmitted from mothers to infants.

Microbial Communities Can Help Trees Adapt to Changing Climates

Tree seedlings that were inoculated with microbes from dry, warm, or cold sites could better survive drought, heat, and cold stress, according to a study in Science.

A Combination of Genetics and Environment Causes Cleft Lip

In a study published in Nature Communications, researchers investigate what combination of genetic and environmental factors come into play to cause cleft lip/palate.