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Abstract The GRAMD genes are involved in maintaining cholesterol homeostasis, apoptosis, cancer and production traits in livestock. A lipid-binding GRAM domain is implicated in lipid transport and metabolism. The functions of GRAMD proteins remain incompletely understood. The aim of the present study was therefore to investigate the associations between six GRAMD genes in cattle using data from the international genomic evaluation of the Interbull InterGenomics Centre and to evaluate genotype-phenotype associations in human, cattle, pig, mouse and, chicken. Genotyping of 55,013 bulls was performed using DNA microarrays and 11 SNPs were mapped to the five GRAMD genes. A phenome-wide association study (PheWAS) tested associations between the 11 SNPs and 36 traits. The integrated analysis of SNP effects, rankings, and clustering patterns revealed their potential for improving cattle productivity, health, and robustness, and established a baseline for the targeted improvement of cattle traits. This study lays the groundwork for functional experiments aimed at uncovering the mechanism of action of GRAMD genes and to evaluate the potential of using GRAMD sequence variants for selection programs in dairy cattle. The study presents an example of how the combination of GWAS and the PheWAS offers a promising toolbox for the systematic functional annotation of vertebrate genomes.

Abstract Chronic lymphocytic leukemia (CLL) is a lymphoproliferative malignancy characterized by the proliferation of functionally mature but incompetent B cells. It is the most prevalent type of leukemia in Western populations, accounting for approximately 25% of new leukemia cases. While recent advances, such as ibrutinib and venetoclax treatment have improved patient outlook, aggressive forms of CLL such as Richter transformation still pose a significant challenge. This discrepancy may be due to the heterogeneity of factors contributing to CLL development at multiple -omics levels. However, information on the omics of CLL is fragmented, hindering multi-omics-based research into potential treatment options. To address this, we aggregated and presented a selection of important aspects of various omics levels of the disease in this review. The purpose of the present literature analysis is to portray examples of CLL studies from different omics levels, including genomics, epigenomics, transcriptomics, epitranscriptomics, proteomics, epiproteomics, metabolomics, glycomics and lipidomics, as well as those identified by multi-omics approaches. The review includes the list of 102 CLL-associated genes with relevant genomics information. While single-omics studies yield substantial and useful data, they omit a significant level of complex biological interplay present in the disease. As multi-omics studies integrate several different layers of data, they may be better suited for complex diseases such as CLL and have thus far yielded promising results. Future multi-omics studies may assist clinicians in improved treatment choices based on CLL subtypes as well as allow the identification of novel biomarkers and targets for treatments.