Biology subjects

Abasht, B.

Publications and source records attributed to Abasht, B..

3 recordsLinked to original sources

bioRxiv2023

Spatial Transcriptomics Reveals Alterations in Perivascular Macrophage Lipid Metabolism: Insights into the onset of Wooden Breast Myopathy in Broiler Chickens

This study aims to use spatial transcriptomics to characterize the cell-type-specific expression profile associated with the microscopic features observed in Wooden Breast myopathy. 1 cm3 muscle sample was dissected from the cranial part of the right pectoralis major muscle from three randomly sampled broiler chickens at 23 days post-hatch and processed with Visium Spatial Gene Expression kits (10X Genomics), followed by high-resolution imaging and sequencing on the Illumina Nextseq 2000 system. WB classification was based on histopathologic features identified. Sequence reads were aligned to the chicken reference genome (Galgal6) and mapped to histological images. Unsupervised K-means clustering and Seurat integrative analysis differentiated histologic features and their specific gene expression pattern, including lipid laden macrophages (LLM), unaffected myofibers, myositis and vasculature. In particular, LLM exhibited reprogramming of lipid metabolism with up-regulated lipid transporters and genes in peroxisome proliferator-activated receptors pathway, possibly through CD36-mediated signaling. Moreover, overexpression of fatty acid binding protein 5 could enhance fatty acid uptake in adjacent veins. In myositic regions, increased expression of cathepsins may play a role in muscle homeostasis and repair by mediating lysosomal activity and apoptosis. A better knowledge of different cell-type interactions at early stages of WB is essential in developing a comprehensive understanding.

pathology↗

bioRxiv2023

Proteomic insight into human directed evolution of the domesticated chicken Gallus gallus.

Chicken domestication began at least 3,500 years ago for purposes of divination, cockfighting, and food. Prior to industrial scale chicken production, domestication selected larger birds with increased egg production. In the mid-20th century companies began intensive selection with the broiler (meat) industry focusing on improved feed conversion, rapid growth, and breast muscle yield. Here we present proteomic analysis comparing the Ross 708 modern broiler line with the UIUC legacy line. Comparing the breast muscle proteome between modern broilers and legacy lines not selected for these growth traits identifies cellular processes that have responded to human directed evolution. Mass spectrometry was used to identify differences in protein levels in the breast muscle of 6-day old chicks from Modern and Legacy lines. The results highlighted elevated levels of stress proteins, ribosomal proteins, and proteins that participate in the innate immune pathway in the Modern chickens. Furthermore, the comparative analyses indicated differences in the levels of proteins involved in multiple biochemical pathways. In particular, the Modern line had elevated levels of proteins affecting the pentose phosphate pathway, TCA cycle, and fatty acid oxidation and reduced protein levels of the first phase of glycolysis. These analyses provide hypotheses linking the morphometric changes driven by human directed selection to biochemical pathways. The results also have implications for the onset of Wooden Breast disease that arose due to selection for rapid breast muscle growth and is a major problem in the poultry industry.

evolutionary biology↗

bioRxiv2019

VARIANT ANALYSIS PIPELINE FOR ACCURATE DETECTION OF GENOMIC VARIANTS FROM TRANSCRIPTOME SEQUENCING DATA.

The wealth of information deliverable from transcriptome sequencing (RNA-seq) is significant, however current applications for variant detection still remain a challenge due to the complexity of the transcriptome. Given the ability of RNA-seq to reveal active regions of the genome, detection of RNA-seq SNPs can prove valuable in understanding the phenotypic diversity between populations. Thus, we present a novel computational workflow named VAP (Variant Analysis Pipeline) that takes advantage of multiple RNA-seq splice aware aligners to call SNPs in non-human models using RNA-seq data only. We applied VAP to RNA-seq from a highly inbred chicken line and achieved >97% precision and >99% sensitivity when compared with the matching whole genome sequencing (WGS) data. Over 65% of WGS coding variants were identified from RNA-seq. Further, our results discovered SNPs resulting from post translational modifications, such as RNA editing, which may reveal potentially functional variation that would have otherwise been missed in genomic data. Even with the limitation in detecting variants in expressed regions only, our method proves to be a reliable alternative for SNP identification using RNA-seq data.

bioinformatics↗