SNCA Gene Polymorphism may Contribute to an Increased Risk of Alzheimer's Disease

Surveying the landscape of RNA isoform diversity and expression across 9 GTEx tissues using long-read sequencing data

Even though alternative RNA splicing was discovered nearly 50 years ago (1977), we still understand very little about most isoforms arising from a single gene, including in which tissues they are expressed and if their functions differ. Human gene annotations suggest remarkable transcriptional complexity, with approximately 252,798 distinct RNA isoform annotations from 62,710 gene bodies (Ensembl v109; 2023), emphasizing the need to understand their biological effects. For example, 256 gene bodies have ≥50 annotated isoforms and 30 have ≥100, where one protein-coding gene ( MAPK10 ) even has 192 distinct RNA isoform annotations. Whether such isoform diversity results from biological redundancy or spurious alternative splicing (i.e., noise), or whether individual isoforms have specialized functions (even if subtle) remains a mystery for most genes. Recent studies by Aguzzoli-Heberle et al., Leung et al., and Glinos et al. demonstrated long-read RNAseq enables improved RNA isoform quantification for essentially any tissue, cell type, or biological condition ( e.g., disease, development, aging, etc.), making it possible to better assess individual isoform expression and function. While each study provided important discoveries related to RNA isoform diversity, deeper exploration is needed. We sought to quantify and characterize real isoform usage across tissues (compared to annotations). We used long-read RNAseq data from 58 GTEx samples across nine tissues (three brain, two heart, muscle, lung, liver, and cultured fibroblasts) generated by Glinos et al. and found considerable isoform diversity within and across tissues. Cerebellar hemisphere was the most transcriptionally complex tissue (22,522 distinct isoforms; 3,726 unique); liver was least diverse (12,435 distinct isoforms; 1,039 unique). We highlight gene clusters exhibiting high tissue-specific isoform diversity per tissue ( e.g., TPM1 expresses 19 in heart's atrial appendage). We also validated 447 of the 700 new isoforms discovered by Aguzzoli-Heberle et al. and found that 88 were expressed in all nine tissues, while 58 were specific to a single tissue. This study represents a broad survey of the RNA isoform landscape, demonstrating isoform diversity across nine tissues and emphasizes the need to better understand how individual isoforms from a single gene body contribute to human health and disease.

Dear reviewers

We sincerely appreciate the time and effort you are taking to review our manuscript. We recognize it is a substantial commitment and welcome your feedback to ensure this work is accurate and helpful to furthering the field's understanding of the human genome and its relevance to human health and disease. Because we recognize how important it is for all scientists to receive proper credit for their contributions to the field, we specifically invite you to notify us if we failed to cite or give proper credit to any relevant publications, whether they be yours or another group's work. Of course, we also welcome all other feedback and will do our best to respond to your suggestions and concerns. Sincerely,Mark T. W. Ebbert.

Overlaps and divergences between tauopathies and synucleinopathies: a duet of neurodegeneration

Proteinopathy, defined as the abnormal accumulation of proteins that eventually leads to cell death, is one of the most significant pathological features of neurodegenerative diseases. Tauopathies, represented by Alzheimer's disease (AD), and synucleinopathies, represented by Parkinson's disease (PD), show similarities in multiple aspects. AD manifests extrapyramidal symptoms while dementia is also a major sign of advanced PD. We and other researchers have sequentially shown the cross-seeding phenomenon of α-synuclein (α-syn) and tau, reinforcing pathologies between synucleinopathies and tauopathies. The highly overlapping clinical and pathological features imply shared pathogenic mechanisms between the two groups of disease. The diagnostic and therapeutic strategies seemingly appropriate for one distinct neurodegenerative disease may also apply to a broader spectrum. Therefore, a clear understanding of the overlaps and divergences between tauopathy and synucleinopathy is critical for unraveling the nature of the complicated associations among neurodegenerative diseases. In this review, we discuss the shared and diverse characteristics of tauopathies and synucleinopathies from aspects of genetic causes, clinical manifestations, pathological progression and potential common therapeutic approaches targeting the pathology, in the aim to provide a timely update for setting the scheme of disease classification and provide novel insights into the therapeutic development for neurodegenerative diseases.

Proteomic profile of human gingival crevicular fluid reveals specific biological and molecular processes during clinical progression of periodontitis

BACKGROUND AND OBJECTIVE

There is no clear understanding of molecular events occurring in the periodontal microenvironment during clinical disease progression. Our aim was to explore qualitative and quantitative differences in gingival crevicular fluid (GCF) protein profiles from patients diagnosed with periodontitis between non-progressive and progressive periodontal sites.

METHODS

Five systemically healthy patients diagnosed with periodontitis were monitored weekly in their progression of the disease and GCF samples from 10 candidate sites were obtained. Two groups of five sites, matched from an equal number of teeth, were selected from the five patients: Progression (PG) and Non-Progression (NP). Global protein identification was performed with high-throughput proteomic approaches and label-free analysis determined their relative abundances. Proteins were identified by Proteome Discoverer v2.4 and searched against human SwissProt protein databases. Enrichment bioinformatic analyses were performed in STRING-DB and ShinyGO environment.

RESULTS

1504 and 1500 proteins were identified in NP and PG respectively. Forty-eight proteins were exclusively identified in PG, while 52 were identified in NP. Moreover, 35 proteins were more abundant in PG and 29 proteins in NP (twofold change, p < .05). The NP group was mainly represented by proteins from "response to biotic stimuli and other organisms," "processes of cell death regulation," "peptidase regulation," "protein ubiquitination," and "ribosomal activity" GO categories. The most represented GO categories of the PG group were "assembly of multiprotein complexes," "catabolic processes," "lipid metabolism," and "binding to hemoglobin and haptoglobin."

CONCLUSIONS

There are quantitative and qualitative differences in the proteome of GCF from periodontal sites according to the status of clinical progression of periodontitis. Progressive periodontitis sites are characterized by a protein profile associated with catabolic processes, immune response, and response to cellular stress, while stable periodontitis sites show a protein profile mainly related to wound repair and healing processes, cell death regulation, and chaperone-mediated autophagy. Understanding the etiopathogenic role of these profiles in progressive periodontitis may help to develop new diagnostic and therapeutic approaches.

Analysis of rare Parkinson's disease variants in millions of people

Objective

Although many rare variants have been reportedly associated with Parkinson's disease (PD), many have not been replicated or have failed to replicate. Here, we conduct a large-scale replication of rare PD variants.

Methods

We assessed a total of 27,590 PD cases, 6,701 PD proxies, and 3,106,080 controls from three data sets: 23andMe, Inc., UK Biobank, and AMP-PD. Based on well-known PD genes, 834 variants of interest were selected from the ClinVar annotated 23andMe dataset. We performed a meta-analysis using summary statistics of all three studies.

Results

The meta-analysis resulted in 11 significant variants after Bonferroni correction, including variants in GBA1 and LRRK2. At least 9 previously reported pathogenic or risk variants for PD did not pass Bonferroni correction in this analysis.

Conclusions

Here, we provide the largest rare variant meta-analysis to date, providing thorough information of variants confirmed, newly identified, or rebutted for their association with PD.

Alpha-synuclein: a pathological factor with Aβ and tau and biomarker in Alzheimer's disease

BACKGROUND

Alpha-synuclein (α-syn) is considered the main pathophysiological protein component of Lewy bodies in synucleinopathies. α-Syn is an intrinsically disordered protein (IDP), and several types of structural conformations have been reported, depending on environmental factors. Since IDPs may have distinctive functions depending on their structures, α-syn can play different roles and interact with several proteins, including amyloid-beta (Aβ) and tau, in Alzheimer's disease (AD) and other neurodegenerative disorders.

MAIN BODY

In previous studies, α-syn aggregates in AD brains suggested a close relationship between AD and α-syn. In addition, α-syn directly interacts with Aβ and tau, promoting mutual aggregation and exacerbating the cognitive decline. The interaction of α-syn with Aβ and tau presented different consequences depending on the structural forms of the proteins. In AD, α-syn and tau levels in CSF were both elevated and revealed a high positive correlation. Especially, the CSF α-syn concentration was significantly elevated in the early stages of AD. Therefore, it could be a diagnostic marker of AD and help distinguish AD from other neurodegenerative disorders by incorporating other biomarkers.

CONCLUSION

The overall physiological and pathophysiological functions, structures, and genetics of α-syn in AD are reviewed and summarized. The numerous associations of α-syn with Aβ and tau suggested the significance of α-syn, as a partner of the pathophysiological roles in AD. Understanding the involvements of α-syn in the pathology of Aβ and tau could help address the unresolved issues of AD. In particular, the current status of the CSF α-syn in AD recommends it as an additional biomarker in the panel for AD diagnosis.

The Neurodegenerative Elderly Syndrome (NES) hypothesis: Alzheimer and Parkinson are two faces of the same disease

Increasing evidence suggests that Alzheimer's disease (AD) and Parkinson's disease (PD) share monoamine and alpha-synuclein (αSyn) dysfunctions, often beginning years before clinical manifestations onset. The triggers for these impairments and the causes leading these early neurodegenerative processes to become AD or PD remain unclear. We address these issues by proposing a radically new perspective to frame AD and PD: they are different manifestations of one only disease we call "Neurodegenerative Elderly Syndrome (NES)". NES goes through three phases. The seeding stage, which starts years before clinical signs, and where the part of the brain-body affected by the initial αSyn and monoamine dysfunctions, influences the future possible progression of NES towards PD or AD. The compensatory stage, where the clinical symptoms are still silent thanks to compensatory mechanisms keeping monoamine concentrations homeostasis. The bifurcation stage, where NES becomes AD or PD. We present recent literature supporting NES and discuss how this hypothesis could radically change the comprehension of AD and PD comorbidities and the design of novel system-level diagnostic and therapeutic actions.

Neurodegenerative Diseases: From Dysproteostasis, Altered Calcium Signalosome to Selective Neuronal Vulnerability to AAV-Mediated Gene Therapy

Despite intense research into the multifaceted etiology of neurodegenerative diseases (ND), they remain incurable. Here we provide a brief overview of several major ND and explore novel therapeutic approaches. Although the cause (s) of ND are not fully understood, the accumulation of misfolded/aggregated proteins in the brain is a common pathological feature. This aggregation may initiate disruption of Ca⁺⁺ signaling, which is an early pathological event leading to altered dendritic structure, neuronal dysfunction, and cell death. Presently, ND gene therapies remain unidimensional, elusive, and limited to modifying one pathological feature while ignoring others. Considering the complexity of signaling cascades in ND, we discuss emerging therapeutic concepts and suggest that deciphering the molecular mechanisms involved in dendritic pathology may broaden the phenotypic spectrum of ND treatment. An innovative multiplexed gene transfer strategy that employs silencing and/or over-expressing multiple effectors could preserve vulnerable neurons before they are lost. Such therapeutic approaches may extend brain health span and ameliorate burdensome chronic disease states.

Mutations in GBA, SNCA, and VPS35 are not associated with Alzheimer's disease in a Chinese population: a case-control study

SNCA, GBA, and VPS35 are three common genes associated with Parkinson’s disease. Previous studies have shown that these three genes may be associated with Alzheimer’s disease (AD). However, it is unclear whether these genes increase the risk of AD in Chinese populations. In this study, we used a targeted gene sequencing panel to screen all the exon regions and the nearby sequences of GBA, SNCA, and VPS35 in a cohort including 721 AD patients and 365 healthy controls from China. The results revealed that neither common variants nor rare variants of these three genes were associated with AD in a Chinese population. These findings suggest that the mutations in GBA, SNCA, and VPS35 are not likely to play an important role in the genetic susceptibility to AD in Chinese populations. The study was approved by the Ethics Committee of Xiangya Hospital, Central South University, China on March 9, 2016 (approval No. 201603198).

A multitude of signaling pathways associated with Alzheimer's disease and their roles in AD pathogenesis and therapy

The exact molecular mechanisms associated with Alzheimer's disease (AD) pathology continue to represent a mystery. In the past decades, comprehensive data were generated on the involvement of different signaling pathways in the AD pathogenesis. However, the utilization of signaling pathways as potential targets for the development of drugs against AD is rather limited due to the immense complexity of the brain and intricate molecular links between these pathways. Therefore, finding a correlation and cross-talk between these signaling pathways and establishing different therapeutic targets within and between those pathways are needed for better understanding of the biological events responsible for the AD-related neurodegeneration. For example, autophagy is a conservative cellular process that shows link with many other AD-related pathways and is crucial for maintenance of the correct cellular balance by degrading AD-associated pathogenic proteins. Considering the central role of autophagy in AD and its interplay with many other pathways, the finest therapeutic strategy to fight against AD is the use of autophagy as a target. As an essential step in this direction, this comprehensive review represents recent findings on the individual AD-related signaling pathways, describes key features of these pathways and their cross-talk with autophagy, represents current drug development, and introduces some of the multitarget beneficial approaches and strategies for the therapeutic intervention of AD.

Genetics of synucleins in neurodegenerative diseases

The SNCA locus currently has an indisputable role in Parkinson's disease and other synucleinopathies. The role of genetic variability in the other members of the synuclein family (SNCB and SNCG) in disease is far less clear. In this review, we critically assess the pathogenicity, main characteristics, and roles of genetic variants in these genes reported to be causative of synucleinopathies. We also summarize the different association signals identified in the SNCA locus that have been associated with risk for disease. We take a bird's eye view of the variability currently reported in the general population for the three genes and use these data to infer on the potential relationship between each of the genes and human disease.

The biological pathways of Alzheimer disease: a review

Alzheimer disease is a progressive neurodegenerative disorder, mainly affecting older people, which severely impairs patients' quality of life. In the recent years, the number of affected individuals has seen a rapid increase. It is estimated that up to 107 million subjects will be affected by 2050 worldwide. Research in this area has revealed a lot about the biological and environmental underpinnings of Alzheimer, especially its correlation with β-Amyloid and Tau related mechanics; however, the precise molecular events and biological pathways behind the disease are yet to be discovered. In this review, we focus our attention on the biological mechanics that may lie behind Alzheimer development. In particular, we briefly describe the genetic elements and discuss about specific biological processes potentially associated with the disease.

Viral Induced Oxidative and Inflammatory Response in Alzheimer's Disease Pathogenesis with Identification of Potential Drug Candidates: A Systematic Review using Systems Biology Approach

Alzheimer's disease (AD) is genetically complex with multifactorial etiology. Here, we aim to identify the potential viral pathogens leading to aberrant inflammatory and oxidative stress response in AD along with potential drug candidates using systems biology approach. We retrieved protein interactions of amyloid precursor protein (APP) and tau protein (MAPT) from NCBI and genes for oxidative stress from NetAge, for inflammation from NetAge and InnateDB databases. Genes implicated in aging were retrieved from GenAge database and two GEO expression datasets. These genes were individually used to create protein-protein interaction network using STRING database (score≥0.7). The interactions of candidate genes with known viruses were mapped using virhostnet v2.0 database. Drug molecules targeting candidate genes were retrieved using the Drug- Gene Interaction Database (DGIdb). Data mining resulted in 2095 APP, 116 MAPT, 214 oxidative stress, 1269 inflammatory genes. After STRING PPIN analysis, 404 APP, 109 MAPT, 204 oxidative stress and 1014 inflammation related high confidence proteins were identified. The overlap among all datasets yielded eight common markers (AKT1, GSK3B, APP, APOE, EGFR, PIN1, CASP8 and SNCA). These genes showed association with hepatitis C virus (HCV), Epstein- Barr virus (EBV), human herpes virus 8 and Human papillomavirus (HPV). Further, screening of drugs targeting candidate genes, and possessing anti-inflammatory property, antiviral activity along with a suggested role in AD pathophysiology yielded 12 potential drug candidates. Our study demonstrated the role of viral etiology in AD pathogenesis by elucidating interaction of oxidative stress and inflammation causing candidate genes with common viruses along with the identification of potential AD drug candidates.

Multi-Loop Model of Alzheimer Disease: An Integrated Perspective on the Wnt/GSK3β, α-Synuclein, and Type 3 Diabetes Hypotheses

As the prevalence of Alzheimer disease (AD) continues to rise unabated, new models have been put forth to improve our understanding of this devastating condition. Although individual models may have their merits, integrated models may prove more valuable. Indeed, the reliable failures of monotherapies for AD, and the ensuing surrender of major drug companies, suggests that an integrated perspective may be necessary if we are to invent multifaceted treatments that could ultimately prove more successful. In this review article, we discuss the Wnt/Glycogen Synthase Kinase 3β (GSK3β), α-synuclein, and type 3 diabetes hypotheses of AD, and their deep interconnection, in order to foster the integrative thinking that may be required to reach a solution for the coming neurological epidemic.

Disease Pathway Cut for Multi-Target drugs

Background

Biomarker discovery studies have been moving the focus from a single target gene to a set of target genes. However, the number of target genes in a drug should be minimum to avoid drug side-effect or toxicity. But still, the set of target genes should effectively block all possible paths of disease progression.

Methods

In this article, we propose a network based computational analysis for target gene identification for multi-target drugs. The min-cut algorithm is employed to cut all the paths from onset genes to apoptotic genes on a disease pathway. If the pathway network is completely disconnected, development of disease will not further go on. The genes corresponding to the end points of the cutting edges are identified as candidate target genes for a multi-target drug.

Results and conclusions

The proposed method was applied to 10 disease pathways. In total, thirty candidate genes were suggested. The result was validated with gene set enrichment analysis software, PubMed literature review and de facto drug targets.

Intrinsic-overlapping co-expression module detection with application to Alzheimer's Disease

Genes interact with each other and may cause perturbation in the molecular pathways leading to complex diseases. Often, instead of any single gene, a subset of genes interact, forming a network, to share common biological functions. Such a subnetwork is called a functional module or motif. Identifying such modules and central key genes in them, that may be responsible for a disease, may help design patient-specific drugs. In this study, we consider the neurodegenerative Alzheimer's Disease (AD) and identify potentially responsible genes from functional motif analysis. We start from the hypothesis that central genes in genetic modules are more relevant to a disease that is under investigation and identify hub genes from the modules as potential marker genes. Motifs or modules are often non-exclusive or overlapping in nature. Moreover, they sometimes show intrinsic or hierarchical distributions with overlapping functional roles. To the best of our knowledge, no prior work handles both the situations in an integrated way. We propose a non-exclusive clustering approach, CluViaN (Clustering Via Network) that can detect intrinsic as well as overlapping modules from gene co-expression networks constructed using microarray expression profiles. We compare our method with existing methods to evaluate the quality of modules extracted. CluViaN reports the presence of intrinsic and overlapping motifs in different species not reported by any other research. We further apply our method to extract significant AD specific modules using CluViaN and rank them based the number of genes from a module involved in the disease pathways. Finally, top central genes are identified by topological analysis of the modules. We use two different AD phenotype data for experimentation. We observe that central genes, namely PSEN1, APP, NDUFB2, NDUFA1, UQCR10, PPP3R1 and a few more, play significant roles in the AD. Interestingly, our experiments also find a hub gene, PML, which has recently been reported to play a role in plasticity, circadian rhythms and the response to proteins which can cause neurodegenerative disorders. MUC4, another hub gene that we find experimentally is yet to be investigated for its potential role in AD. A software implementation of CluViaN in Java is available for download at https://sites.google.com/site/swarupnehu/publications/resources/CluViaN Software.rar.

Early Life Stress and Epigenetics in Late-onset Alzheimer's Dementia: A Systematic Review

Involvement of life stress in Late-Onset Alzheimer's Disease (LOAD) has been evinced in longitudinal cohort epidemiological studies, and endocrinologic evidence suggests involvements of catecholamine and corticosteroid systems in LOAD. Early Life Stress (ELS) rodent models have successfully demonstrated sequelae of maternal separation resulting in LOAD-analogous pathology, thereby supporting a role of insulin receptor signalling pertaining to GSK-3beta facilitated tau hyper-phosphorylation and amyloidogenic processing. Discussed are relevant ELS studies, and findings from three mitogen-activated protein kinase pathways (JNK/SAPK pathway, ERK pathway, p38/MAPK pathway) relevant for mediating environmental stresses. Further considered were the roles of autophagy impairment, neuroinflammation, and brain insulin resistance. For the meta-analytic evaluation, 224 candidate gene loci were extracted from reviews of animal studies of LOAD pathophysiological mechanisms, of which 60 had no positive results in human LOAD association studies. These loci were combined with 89 gene loci confirmed as LOAD risk genes in previous GWAS and WES. Of the 313 risk gene loci evaluated, there were 35 human reports on epigenomic modifications in terms of methylation or histone acetylation. 64 microRNA gene regulation mechanisms were published for the compiled loci. Genomic association studies support close relations of both noradrenergic and glucocorticoid systems with LOAD. For HPA involvement, a CRHR1 haplotype with MAPT was described, but further association of only HSD11B1 with LOAD found; however, association of FKBP1 and NC3R1 polymorphisms was documented in support of stress influence to LOAD. In the brain insulin system, IGF2R, INSR, INSRR, and plasticity regulator ARC, were associated with LOAD. Pertaining to compromised myelin stability in LOAD, relevant associations were found for BIN1, RELN, SORL1, SORCS1, CNP, MAG, and MOG. Regarding epigenetic modifications, both methylation variability and de-acetylation were reported for LOAD. The majority of up-to-date epigenomic findings include reported modifications in the well-known LOAD core pathology loci MAPT, BACE1, APP (with FOS, EGR1), PSEN1, PSEN2, and highlight a central role of BDNF. Pertaining to ELS, relevant loci are FKBP5, EGR1, GSK3B; critical roles of inflammation are indicated by CRP, TNFA, NFKB1 modifications; for cholesterol biosynthesis, DHCR24; for myelin stability BIN1, SORL1, CNP; pertaining to (epi)genetic mechanisms, hTERT, MBD2, DNMT1, MTHFR2. Findings on gene regulation were accumulated for BACE1, MAPK signalling, TLR4, BDNF, insulin signalling, with most reports for miR-132 and miR-27. Unclear in epigenomic studies remains the role of noradrenergic signalling, previously demonstrated by neuropathological findings of childhood nucleus caeruleus degeneration for LOAD tauopathy.

Autophagy and Alzheimer's Disease: From Molecular Mechanisms to Therapeutic Implications

Alzheimer’s disease (AD) is the most common cause of progressive dementia in the elderly. It is characterized by a progressive and irreversible loss of cognitive abilities and formation of senile plaques, composed mainly of amyloid β (Aβ), and neurofibrillary tangles (NFTs), composed of tau protein, in the hippocampus and cortex of afflicted humans. In brains of AD patients the metabolism of Aβ is dysregulated, which leads to the accumulation and aggregation of Aβ. Metabolism of Aβ and tau proteins is crucially influenced by autophagy. Autophagy is a lysosome-dependent, homeostatic process, in which organelles and proteins are degraded and recycled into energy. Thus, dysfunction of autophagy is suggested to lead to the accretion of noxious proteins in the AD brain. In the present review, we describe the process of autophagy and its importance in AD. Additionally, we discuss mechanisms and genes linking autophagy and AD, i.e., the mTOR pathway, neuroinflammation, endocannabinoid system, ATG7, BCL2, BECN1, CDK5, CLU, CTSD, FOXO1, GFAP, ITPR1, MAPT, PSEN1, SNCA, UBQLN1, and UCHL1. We also present pharmacological agents acting via modulation of autophagy that may show promise in AD therapy. This review updates our knowledge on autophagy mechanisms proposing novel therapeutic targets for the treatment of AD.

CNV discovery for milk composition traits in dairy cattle using whole genome resequencing

Background

Copy number variations (CNVs) are important and widely distributed in the genome. CNV detection opens a new avenue for exploring genes associated with complex traits in humans, animals and plants. Herein, we present a genome-wide assessment of CNVs that are potentially associated with milk composition traits in dairy cattle.

Results

In this study, CNVs were detected based on whole genome re-sequencing data of eight Holstein bulls from four half- and/or full-sib families, with extremely high and low estimated breeding values (EBVs) of milk protein percentage and fat percentage. The range of coverage depth per individual was 8.2–11.9×. Using CNVnator, we identified a total of 14,821 CNVs, including 5025 duplications and 9796 deletions. Among them, 487 differential CNV regions (CNVRs) comprising ~8.23 Mb of the cattle genome were observed between the high and low groups. Annotation of these differential CNVRs were performed based on the cattle genome reference assembly (UMD3.1) and totally 235 functional genes were found within the CNVRs. By Gene Ontology and KEGG pathway analyses, we found that genes were significantly enriched for specific biological functions related to protein and lipid metabolism, insulin/IGF pathway-protein kinase B signaling cascade, prolactin signaling pathway and AMPK signaling pathways. These genes included INS, IGF2, FOXO3, TH, SCD5, GALNT18, GALNT16, ART3, SNCA and WNT7A, implying their potential association with milk protein and fat traits. In addition, 95 CNVRs were overlapped with 75 known QTLs that are associated with milk protein and fat traits of dairy cattle (Cattle QTLdb).

Conclusions

In conclusion, based on NGS of 8 Holstein bulls with extremely high and low EBVs for milk PP and FP, we identified a total of 14,821 CNVs, 487 differential CNVRs between groups, and 10 genes, which were suggested as promising candidate genes for milk protein and fat traits.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-3636-3) contains supplementary material, which is available to authorized users.