Hmga2 deficiency is associated with allometric growth retardation, infertility, and behavioral abnormalities in mice

Decoding high mobility group A2 protein expression regulation and implications in human cancers

High Mobility Group A2 (HMGA2) oncofetal proteins are a distinct category of Transcription Factors (TFs) known as "architectural factors" due to their lack of direct transcriptional activity. Instead, they modulate the three-dimensional structure of chromatin by binding to AT-rich regions in the minor grooves of DNA through their AT-hooks. This binding allows HMGA2 to interact with other proteins and different regions of DNA, thereby regulating the expression of numerous genes involved in carcinogenesis. Consequently, multiple mechanisms exist to finely control HMGA2 protein expression at various transcriptional levels, ensuring precise concentration adjustments to maintain cellular homeostasis. During embryonic development, HMGA2 protein is highly expressed but becomes absent in adult tissues. However, recent studies have revealed its re-elevation in various cancer types. Extensive research has demonstrated the involvement of HMGA2 protein in carcinogenesis at multiple levels. It intervenes in crucial processes such as cell cycle regulation, apoptosis, angiogenesis, epithelial-to-mesenchymal transition, cancer cell stemness, and DNA damage repair mechanisms, ultimately promoting cancer cell survival. This comprehensive review provides insights into the HMGA2 protein, spanning from the genetic regulation to functional protein behavior. It highlights the significant mechanisms governing HMGA2 gene expression and elucidates the molecular roles of HMGA2 in the carcinogenesis process.

Shared molecular mechanisms and transdiagnostic potential of neurodevelopmental disorders and immune disorders

The co-occurrence and familial clustering of neurodevelopmental disorders and immune disorders suggest shared genetic risk factors. Based on genome-wide association summary statistics from five neurodevelopmental disorders and four immune disorders, we conducted genome-wide, local genetic correlation and polygenic overlap analysis. We further performed a cross-trait GWAS meta-analysis. Pleotropic loci shared between the two categories of diseases were mapped to candidate genes using multiple algorithms and approaches. Significant genetic correlations were observed between neurodevelopmental disorders and immune disorders, including both positive and negative correlations. Neurodevelopmental disorders exhibited higher polygenicity compared to immune disorders. Around 50%-90% of genetic variants of the immune disorders were shared with neurodevelopmental disorders. The cross-trait meta-analysis revealed 154 genome-wide significant loci, including 8 novel pleiotropic loci. Significant associations were observed for 30 loci with both types of diseases. Pathway analysis on the candidate genes at these loci revealed common pathways shared by the two types of diseases, including neural signaling, inflammatory response, and PI3K-Akt signaling pathway. In addition, 26 of the 30 lead SNPs were associated with blood cell traits. Neurodevelopmental disorders exhibit complex polygenic architecture, with a subset of individuals being at a heightened genetic risk for both neurodevelopmental and immune disorders. The identification of pleiotropic loci has important implications for exploring opportunities for drug repurposing, enabling more accurate patient stratification, and advancing genomics-informed precision in the medical field of neurodevelopmental disorders.

A Recql5 mutant facilitates complex CRISPR/Cas9-mediated chromosomal engineering in mouse zygotes

Complex chromosomal rearrangements (CCRs) are often observed in clinical samples from patients with cancer and congenital diseases but are difficult to induce experimentally. Here, we report the first success in establishing animal models for CCRs. Mutation in Recql5, a crucial member of the DNA helicase RecQ family involved in DNA replication, transcription, and repair, enabled CRISPR/Cas9-mediated CCRs, establishing a mouse model containing triple fusion genes and megabase-sized inversions. Some of these structural features of individual chromosomal rearrangements use template switching and microhomology-mediated break-induced replication mechanisms and are reminiscent of the newly described phenomenon "chromoanasynthesis." These data show that Recql5 mutant mice could be a powerful tool to analyze the pathogenesis of CCRs (particularly chromoanasynthesis) whose underlying mechanisms are poorly understood. The Recql5 mutants generated in this study are to be deposited at key animal research facilities, thereby making them accessible for future research on CCRs.

Hybrid de novo and haplotype-resolved genome assembly of Vechur cattle - elucidating genetic variation

Cattle contribute to the nutritional needs and economy of a place. The performance and fitness of cattle depend on the response and adaptation to local climatic conditions. Genomic and genetic studies are important for advancing cattle breeding, and availability of relevant reference genomes is essential. In the present study, the genome of a Vechur calf was sequenced on both short-read Illumina and long-read Nanopore sequencing platforms. The hybrid de novo assembly approach was deployed to obtain an average contig length of 1.97 Mbp and an N50 of 4.94 Mbp. By using a short-read genome sequence of the corresponding sire and dam, a haplotype-resolved genome was also assembled. In comparison to the taurine reference genome, we found 28,982 autosomal structural variants and 16,926,990 SNVs, with 883,544 SNVs homozygous in the trio samples. Many of these SNPs have been reported to be associated with various QTLs including growth, milk yield, and milk fat content, which are crucial determinants of cattle production. Furthermore, population genotype data analysis indicated that the present sample belongs to an Indian cattle breed forming a unique cluster of Bos indicus. Subsequent FST analysis revealed differentiation of the Vechur cattle genome at multiple loci, especially those regions related to whole body growth and cell division, especially IGF1, HMGA2, RRM2, and CD68 loci, suggesting a possible role of these genes in its small stature and better disease resistance capabilities in comparison with the local crossbreeds. This provides an opportunity to select and engineer cattle breeds optimized for local conditions.

Characterization of HMGA2 variants expands the spectrum of Silver-Russell syndrome

Silver-Russell syndrome (SRS) is a heterogeneous disorder characterized by intrauterine and postnatal growth retardation. HMGA2 variants are a rare cause of SRS and its functional role in human linear growth is unclear. Patients with suspected SRS negative for 11p15LOM/mUPD7 underwent whole-exome and/or targeted-genome sequencing. Mutant HMGA2 protein expression and nuclear localization were assessed. Two Hmga2-knockin mouse models were generated. Five clinical SRS patients harbored HMGA2 variants with differing functional impacts: 2 stop-gain nonsense variants (c.49G>T, c.52C>T), c.166A>G missense variant, and 2 frameshift variants (c.144delC, c.145delA) leading to an identical, extended-length protein. Phenotypic features were highly variable. Nuclear localization was reduced/absent for all variants except c.166A>G. Homozygous knockin mice recapitulating the c.166A>G variant (Hmga2K56E) exhibited a growth-restricted phenotype. An Hmga2Ter76-knockin mouse model lacked detectable full-length Hmga2 protein, similarly to patient 3 and 5 variants. These mice were infertile, with a pygmy phenotype. We report a heterogeneous group of individuals with SRS harboring variants in HMGA2 and describe the first Hmga2 missense knockin mouse model (Hmga2K56E) to our knowledge causing a growth-restricted phenotype. In patients with clinical features of SRS but negative genetic screening, HMGA2 should be included in next-generation sequencing testing approaches.

Dynamic Expression Profile of Follicles at Different Stages in High- and Low-Production Laying Hens

Improving the efficiency of hens and extending the egg-laying cycle require maintaining high egg production in the later stages. The ovarian follicles, as the primary functional units for ovarian development and oocyte maturation, play a crucial role in regulating the continuous ovulation of hens. The egg production rate of laying hens is mostly affected by proper follicle growth and ovulation in the ovaries. The objective of this study was to identify the key genes and signaling pathways involved in the development of ovarian follicles in Taihang hens through transcriptome screening. In this study, RNA sequencing was used to compare and analyze the transcriptomes of ovarian follicles at four developmental stages: small white follicles (SWF), small yellow follicles (SYF), F5 follicles, and F2 follicles, from two groups: the high continual production group (H-Group) and the low continual production group (L-Group). A total of 24 cDNA libraries were constructed, and significant differential expression of 96, 199, 591, and 314 mRNAs was detected in the SWF, SYF, F5, and F2 follicles of the H and L groups, respectively. Based on the results of GO and KEGG enrichment analyses, each stage of follicle growth possesses distinct molecular genetic features, which have important effects on follicle development and significantly promote the formation of continuous production traits through the biosynthesis of steroid hormones, cytokine-cytokine receptor interaction, and neuroactive ligand-receptor interaction. Additionally, through STEM analysis, we identified 59 DEGs, including ZP4, KCNH1, IGFs, HMGA2, and CDH1, potentially associated with follicular development within four significant modules. This study represents the first transcriptome investigation of follicles in hens with high and low egg-producing characteristics at four crucial developmental stages. These findings provide important molecular evidence for understanding the regulation of follicular development and its variations.

Multitrait meta-analyses identify potential candidate genes for growth-related traits in Holstein heifers

Understanding the underlying pleiotropic relationships among growth and body size traits is important for refining breeding strategies in dairy cattle for optimal body size and growth rate. Therefore, we performed single-trait GWAS for monthly-recorded body weight (BW), hip height, body length, and chest girth from birth to 12 mo of age in Holstein animals, followed by stepwise multiple regression of independent or lowly-linked markers from GWAS loci using conditional and joint association analyses (COJO). Subsequently, we conducted a multitrait meta-analysis to detect pleiotropic markers. Based on the single-trait GWAS, we identified 170 significant SNPs, in which 59 of them remained significant after the COJO analyses. The most significant SNP, located at BTA7:3,676,741, explained 2.93% of the total phenotypic variance for BW6 (BW at 6 mo of age). We identified 17 SNPs with potential pleiotropic effects based on the multitrait meta-analyses, which resulted in 3 additional SNPs in comparison to those detected based on the single-trait GWAS. The identified quantitative trait loci regions overlap with genes known to influence human growth-related traits. According to positional and functional analyses, we proposed HMGA2, HNF4G, MED13L, BHLHE40, FRZB, DMP1, TRIB3, and GATAD2A as important candidate genes influencing the studied traits. The combination of single-trait GWAS and meta-analyses of GWAS results improved the efficiency of detecting associated SNPs, and provided new insights into the genetic mechanisms of growth and development in Holstein cattle.

A scalable approach to characterize pleiotropy across thousands of human diseases and complex traits using GWAS summary statistics

Genome-wide association studies (GWASs) across thousands of traits have revealed the pervasive pleiotropy of trait-associated genetic variants. While methods have been proposed to characterize pleiotropic components across groups of phenotypes, scaling these approaches to ultra-large-scale biobanks has been challenging. Here, we propose FactorGo, a scalable variational factor analysis model to identify and characterize pleiotropic components using biobank GWAS summary data. In extensive simulations, we observe that FactorGo outperforms the state-of-the-art (model-free) approach tSVD in capturing latent pleiotropic factors across phenotypes while maintaining a similar computational cost. We apply FactorGo to estimate 100 latent pleiotropic factors from GWAS summary data of 2,483 phenotypes measured in European-ancestry Pan-UK BioBank individuals (N = 420,531). Next, we find that factors from FactorGo are more enriched with relevant tissue-specific annotations than those identified by tSVD (p = 2.58E-10) and validate our approach by recapitulating brain-specific enrichment for BMI and the height-related connection between reproductive system and muscular-skeletal growth. Finally, our analyses suggest shared etiologies between rheumatoid arthritis and periodontal condition in addition to alkaline phosphatase as a candidate prognostic biomarker for prostate cancer. Overall, FactorGo improves our biological understanding of shared etiologies across thousands of GWASs.

Genome-Wide Association and Pathway Analysis of Carcass and Meat Quality Traits in Karachai Young Goats

Goats with diverse economic phenotypic traits play an important role in animal husbandry. However, the genetic mechanisms underlying complex phenotypic traits are unclear in goats. Genomic studies of variations provided a lens to identify functional genes. The work aimed to search for candidate genes related to body measurements and body weight of Karachai goats and develop an experimental PCR-RV test system for genotyping significant SNPs. Comparison of GWAS results for ages 4 and 8 months revealed 58 common SNPs for significant genotypes. 11 common SNPs were identified for body weight, 4 SNPs-for group of traits withers height, rump height, body length, 2 SNPs-for withers height and rump height, 1 SNP-for body length and chest depth. Structural annotation of genomic regions covering a window of ±0.20 Mb showed the presence of 288 genes; 52 of them had the described functions in accordance with gene ontology. The main molecular functions of proteins encoded by these genes are the regulation of transcription, cell proliferation, angiogenesis, body growth, fatty acid and lipid metabolism, nervous system development, and spermatogenesis. SNPs common to body weight and localized within a window of ±200 kb from the structural genes CRADD, HMGA2, MSRB3, FUT8, MAX, and RAB15 were selected to create a test system. The study of meat productivity after slaughter and chemical analysis of muscle tissue in Karachai goats at the age of 8 months of different genotypes according to the identified SNPs revealed that rs268269710 is the most promising for further research and use in breeding. The GG genotype is associated with a larger live weight of animals, a larger carcass yield, the content of the boneless part in it, and the ratio of protein and adipose tissue in meat preferred for dietary nutrition. These results will contribute to the genetic improvement of Karachai goats.

Community-wide genome sequencing reveals 30 years of Darwin's finch evolution

A fundamental goal in evolutionary biology is to understand the genetic architecture of adaptive traits. Using whole-genome data of 3955 of Darwin's finches on the Galápagos Island of Daphne Major, we identified six loci of large effect that explain 45% of the variation in the highly heritable beak size of Geospiza fortis, a key ecological trait. The major locus is a supergene comprising four genes. Abrupt changes in allele frequencies at the loci accompanied a strong change in beak size caused by natural selection during a drought. A gradual change in Geospiza scandens occurred across 30 years as a result of introgressive hybridization with G. fortis. This study shows how a few loci with large effect on a fitness-related trait contribute to the genetic potential for rapid adaptive radiation.

A scalable variational approach to characterize pleiotropic components across thousands of human diseases and complex traits using GWAS summary statistics

Genome-wide association studies (GWAS) across thousands of traits have revealed the pervasive pleiotropy of trait-associated genetic variants. While methods have been proposed to characterize pleiotropic components across groups of phenotypes, scaling these approaches to ultra large-scale biobanks has been challenging. Here, we propose FactorGo, a scalable variational factor analysis model to identify and characterize pleiotropic components using biobank GWAS summary data. In extensive simulations, we observe that FactorGo outperforms the state-of-the-art (model-free) approach tSVD in capturing latent pleiotropic factors across phenotypes, while maintaining a similar computational cost. We apply FactorGo to estimate 100 latent pleiotropic factors from GWAS summary data of 2,483 phenotypes measured in European-ancestry Pan-UK BioBank individuals (N=420,531). Next, we find that factors from FactorGo are more enriched with relevant tissue-specific annotations than those identified by tSVD (P=2.58E-10), and validate our approach by recapitulating brain-specific enrichment for BMI and the height-related connection between reproductive system and muscular-skeletal growth. Finally, our analyses suggest novel shared etiologies between rheumatoid arthritis and periodontal condition, in addition to alkaline phosphatase as a candidate prognostic biomarker for prostate cancer. Overall, FactorGo improves our biological understanding of shared etiologies across thousands of GWAS.

Aberrant HMGA2 Expression Sustains Genome Instability That Promotes Metastasis and Therapeutic Resistance in Colorectal Cancer

Colorectal cancer (CRC) is one of the most lethal cancers worldwide, accounting for nearly ~10% of all cancer diagnoses and deaths. Current therapeutic approaches have considerably increased survival for patients diagnosed at early stages; however, ~20% of CRC patients are diagnosed with late-stage, metastatic CRC, where 5-year survival rates drop to 6–13% and treatment options are limited. Genome instability is an enabling hallmark of cancer that confers increased acquisition of genetic alterations, mutations, copy number variations and chromosomal rearrangements. In that regard, research has shown a clear association between genome instability and CRC, as the accumulation of aberrations in cancer-related genes provides subpopulations of cells with several advantages, such as increased proliferation rates, metastatic potential and therapeutic resistance. Although numerous genes have been associated with CRC, few have been validated as predictive biomarkers of metastasis or therapeutic resistance. A growing body of evidence suggests a member of the High-Mobility Group A (HMGA) gene family, HMGA2, is a potential biomarker of metastatic spread and therapeutic resistance. HMGA2 is expressed in embryonic tissues and is frequently upregulated in aggressively growing cancers, including CRC. As an architectural, non-histone chromatin binding factor, it initiates chromatin decompaction to facilitate transcriptional regulation. HMGA2 maintains the capacity for stem cell renewal in embryonic and cancer tissues and is a known promoter of epithelial-to-mesenchymal transition in tumor cells. This review will focus on the known molecular mechanisms by which HMGA2 exerts genome protective functions that contribute to cancer cell survival and chemoresistance in CRC.

Identification of Genomic Regions and Candidate Genes Associated with Body Weight and Body Conformation Traits in Karachai Goats

The objective of this study was to identify the SNPs and candidate genes related to body weight and seven body conformation traits at the age of 8 months in the Russian aboriginal Karachai goats (n = 269) by conducting genome-wide association studies (GWAS), using genotypes generated by Goat SNP BeadChip (Illumina Inc., USA). We identified 241 SNPs, which were significantly associated with the studied traits, including 47 genome-wide SNPs (p < 10−5) and 194 suggestive SNPs (p < 10−4), distributed among all goat autosomes except for autosome 23. Fifty-six SNPs were common for two and more traits (1 SNP for six traits, 2 SNPs for five traits, 12 SNPs for four traits, 20 SNPs for three traits, and 21 SNPs for two traits), while 185 SNPs were associated with single traits. Structural annotation within a window of 0.4 Mb (±0.2 Mb from causal SNPs) revealed 238 candidate genes. The largest number of candidate genes was identified at Chr13 (33 candidate genes for the five traits). The genes identified in our study were previously reported to be associated with growth-related traits in different livestock species. The most significant genes for body weight were CRADD, HMGA2, MSRB3, MAX, HACL1 and RAB15, which regulate growth processes, body sizes, fat deposition, and average daily gains. Among them, the HMGA2 gene is a well-known candidate for prenatal and early postnatal development, and the MSRB3 gene is proposed as a candidate gene affecting the growth performance. APOB, PTPRK, BCAR1, AOAH and ASAH1 genes associated with withers height, rump height and body length, are involved in various metabolic processes, including fatty acid metabolism and lipopolysaccharide catabolism. In addition, WDR70, ZBTB24, ADIPOQ, and SORCS3 genes were linked to chest width. KCNG4 was associated with rump height, body length and chest perimeter. The identified candidate genes can be proposed as molecular markers for growth trait selection for genetic improvement in Karachai goats.