Comparison of actionable events detected in cancer genomes by whole-genome sequencing, in silico whole-exome and mutation panels.

BACKGROUND: Next-generation sequencing is used in cancer research to identify somatic and germline mutations, which can predict sensitivity or resistance to therapies, and may be a useful tool to reveal drug repurposing opportunities between tumour types. Multigene panels are used in clinical practice for detecting targetable mutations. However, the value of clinical whole-exome sequencing (WES) and whole-genome sequencing (WGS) for cancer care is less defined, specifically as the majority of variants found using these technologies are of uncertain significance. PATIENTS AND METHODS: We used the Cancer Genome Interpreter and WGS in 726 tumours spanning 10 cancer types to identify drug repurposing opportunities. We compare the ability of WGS to detect actionable variants, tumour mutation burden (TMB) and microsatellite instability (MSI) by using in silico down-sampled data to mimic WES, a comprehensive sequencing panel and a hotspot mutation panel. RESULTS: We reveal drug repurposing opportunities as numerous biomarkers are shared across many solid tumour types. Comprehensive panels identify the majority of approved actionable mutations, with WGS detecting more candidate actionable mutations for biomarkers currently in clinical trials. Moreover, estimated values for TMB and MSI vary when calculated from WGS, WES and panel data, and are dependent on whether all mutations or only non-synonymous mutations were used. Our results suggest that TMB and MSI thresholds should not only be tumour-dependent, but also be sequencing platform-dependent. CONCLUSIONS: There is a large opportunity to repurpose cancer drugs, and these data suggest that comprehensive sequencing is an invaluable source of information to guide clinical decisions by facilitating precision medicine and may provide a wealth of information for future studies. Furthermore, the sequencing and analysis approach used to estimate TMB may have clinical implications if a hard threshold is used to indicate which patients may respond to immunotherapy.

Whole-genome sequencing reveals clinically relevant insights into the aetiology of familial breast cancers.

BACKGROUND: Whole-genome sequencing (WGS) is a powerful method for revealing the diversity and complexity of the somatic mutation burden of tumours. Here, we investigated the utility of tumour and matched germline WGS for understanding aetiology and treatment opportunities for high-risk individuals with familial breast cancer. PATIENTS AND METHODS: We carried out WGS on 78 paired germline and tumour DNA samples from individuals carrying pathogenic variants in BRCA1 (n = 26) or BRCA2 (n = 22) or from non-carriers (non-BRCA1/2; n = 30). RESULTS: Matched germline/tumour WGS and somatic mutational signature analysis revealed patients with unreported, dual pathogenic germline variants in cancer risk genes (BRCA1/BRCA2; BRCA1/MUTYH). The strategy identified that 100% of tumours from BRCA1 carriers and 91% of tumours from BRCA2 carriers exhibited biallelic inactivation of the respective gene, together with somatic mutational signatures suggestive of a functional deficiency in homologous recombination. A set of non-BRCA1/2 tumours also had somatic signatures indicative of BRCA-deficiency, including tumours with BRCA1 promoter methylation, and tumours from carriers of a PALB2 pathogenic germline variant and a BRCA2 variant of uncertain significance. A subset of 13 non-BRCA1/2 tumours from early onset cases were BRCA-proficient, yet displayed complex clustered structural rearrangements associated with the amplification of oncogenes and pathogenic germline variants in TP53, ATM and CHEK2. CONCLUSIONS: Our study highlights the role that WGS of matched germline/tumour DNA and the somatic mutational signatures can play in the discovery of pathogenic germline variants and for providing supporting evidence for variant pathogenicity. WGS-derived signatures were more robust than germline status and other genomic predictors of homologous recombination deficiency, thus impacting the selection of platinum-based or PARP inhibitor therapy. In this first examination of non-BRCA1/2 tumours by WGS, we illustrate the considerable heterogeneity of these tumour genomes and highlight that complex genomic rearrangements may drive tumourigenesis in a subset of cases.

Quantitative trait loci with sex-specific effects for internal organs weights and hematocrit value in a broiler-layer cross.

Rapid growth in broilers is associated with susceptibility to metabolic disorders such as pulmonary hypertension syndrome (ascites) and sudden death. This study describes a genome search for QTL associated with relative weight of cardio respiratory and metabolically important organs (heart, lungs, liver and gizzard), and hematocrit value in a Brazilian broiler-layer cross. QTL with similar or different effects across sexes were investigated. At 42 days of age after fasted for 6 h, the F2 chickens were weighed and slaughtered. Weights and percentages of the weight relative to BW42 of gizzard, heart, lungs, liver and hematocrit were used in the QTL search. Parental, F1 and F2 individuals were genotyped with 128 genetic markers (127 microsatellites and 1 SNP) covering 22 linkage groups. QTL mapping analyses were carried out using mixed models. A total of 11 genome-wide significant QTL and five suggestive linkages were mapped. Thus, genome-wide significant QTL with similar effects across sexes were mapped to GGA2, 4 and 14 for heart weight, and to GGA2, 8 and 12 for gizzard %. Additionally, five genome-wide significant QTL with different effects across sexes were mapped to GGA 8, 19 and 26 for heart weight; GGA26 for heart % and GGA3 for hematocrit value. Five QTL were detected in chromosomal regions where QTL for similar traits were previously mapped in other F2 chicken populations. Seven novel genome-wide significant QTL are reported here, and 21 positional candidate genes in QTL regions were identified.

Genetic parameters and mapping quantitative trait loci associated with tibia traits in broilers.

Selection among broilers for performance traits is resulting in locomotion problems and bone disorders, once skeletal structure is not strong enough to support body weight in broilers with high growth rates. In this study, genetic parameters were estimated for body weight at 42 days of age (BW42), and tibia traits (length, width, and weight) in a population of broiler chickens. Quantitative trait loci (QTL) were identified for tibia traits to expand our knowledge of the genetic architecture of the broiler population. Genetic correlations ranged from 0.56 ± 0.18 (between tibia length and BW42) to 0.89 ± 0.06 (between tibia width and weight), suggesting that these traits are either controlled by pleiotropic genes or by genes that are in linkage disequilibrium. For QTL mapping, the genome was scanned with 127 microsatellites, representing a coverage of 2630 cM. Eight QTL were mapped on Gallus gallus chromosomes (GGA): GGA1, GGA4, GGA6, GGA13, and GGA24. The QTL regions for tibia length and weight were mapped on GGA1, between LEI0079 and MCW145 markers. The gene DACH1 is located in this region; this gene acts to form the apical ectodermal ridge, responsible for limb development. Body weight at 42 days of age was included in the model as a covariate for selection effect of bone traits. Two QTL were found for tibia weight on GGA2 and GGA4, and one for tibia width on GGA3. Information originating from these QTL will assist in the search for candidate genes for these bone traits in future studies.

The long non-coding RNA Gomafu is acutely regulated in response to neuronal activation and involved in schizophrenia-associated alternative splicing.

Schizophrenia (SZ) is a complex disease characterized by impaired neuronal functioning. Although defective alternative splicing has been linked to SZ, the molecular mechanisms responsible are unknown. Additionally, there is limited understanding of the early transcriptomic responses to neuronal activation. Here, we profile these transcriptomic responses and show that long non-coding RNAs (lncRNAs) are dynamically regulated by neuronal activation, including acute downregulation of the lncRNA Gomafu, previously implicated in brain and retinal development. Moreover, we demonstrate that Gomafu binds directly to the splicing factors QKI and SRSF1 (serine/arginine-rich splicing factor 1) and dysregulation of Gomafu leads to alternative splicing patterns that resemble those observed in SZ for the archetypal SZ-associated genes DISC1 and ERBB4. Finally, we show that Gomafu is downregulated in post-mortem cortical gray matter from the superior temporal gyrus in SZ. These results functionally link activity-regulated lncRNAs and alternative splicing in neuronal function and suggest that their dysregulation may contribute to neurological disorders.

Quantitative trait loci associated with chemical composition of the chicken carcass.

Major objectives of the poultry industry are to increase meat production and to reduce carcass fatness, mainly abdominal fat. Information on growth performance and carcass composition are important for the selection of leaner meat chickens. To enhance our understanding of the genetic architecture underlying the chemical composition of chicken carcasses, an F(2) population developed from a broiler × layer cross was used to map quantitative trait loci (QTL) affecting protein, fat, water and ash contents in chicken carcasses. Two genetic models were applied in the QTL analysis: the line-cross and the half-sib models, both using the regression interval mapping method. Six significant and five suggestive QTL were mapped in the line-cross analysis, and four significant and six suggestive QTL were mapped in the half-sib analysis. A total of eleven QTL were mapped for fat (ether extract), five for protein, four for ash and one for water contents in the carcass using both analyses. No study to date has reported QTL for carcass chemical composition in chickens. Some QTL mapped here for carcass fat content match, as expected, QTL regions previously associated with abdominal fat in the same or in different populations, and novel QTL for protein, ash and water contents in the carcass are presented here. The results described here also reinforce the need for fine mapping and to perform multi-trait analyses to better understand the genetic architecture of these traits.

Heritabilities and genetic correlations for reproductive traits in an F2 reciprocal cross chicken population.

Studies estimating genetic parameters for reproductive traits in chickens can be useful for understanding and improvement of their genetic architecture. A total of 1276 observations of fertility (FERT), hatchability of fertile eggs (HFE) and hatchability of total eggs (HTE) were used to estimate the genetic and phenotypic parameters of 467 females from an F2 population generated by reciprocal crossing between a broiler line and a layer line, which were developed through a poultry genetics breeding program, maintained by Embrapa Swine and Poultry, Concordia, Santa Catarina, Brazil. Estimates of heritability and genetic and phenotypic correlations were obtained using restricted maximum likelihood calculations under the two-trait animal model, including the fixed effect of group (hatching of birds from the same genetic group) and the random additive genetic and residual effects. The mean percentages for FERT, HFE and HTE were 87.91 ± 19.77, 80.07 ± 26.81 and 70.67 ± 28.55%, respectively. The highest heritability estimate (h(2)) was 0.28 ± 0.04 for HTE. Genetic correlations for FERT with HFE (0.43 ± 0.17), HFE with HTE (0.98 ± 0.02) and FERT with HTE (0.69 ± 0.10) were positive and significant. Individuals with high breeding value for HTE would have high breeding values for HFE and FERT because of the high genetic association between them. These results suggest that HTE should be included as a selection criterion in genetic breeding programs to improve the reproductive performance of chickens, because HTE had the highest heritability estimate and high genetic correlation with FERT and HFE, and it is the easiest to measure.

QTL for percentage of carcass and carcass parts in a broiler x layer cross.

An F2 experimental population, developed from a broiler layer cross, was used in a genome scan of QTL for percentage of carcass, carcass parts, shank and head. Up to 649 F2 chickens from four paternal half-sib families were genotyped with 128 genetic markers covering 22 linkage groups. Total map length was 2630 cM, covering approximately 63% of the genome. QTL interval mapping using regression methods was applied to line-cross and half-sib models. Under the line-cross model, 12 genome-wide significant QTL and 17 suggestive linkages for percentages of carcass parts, shank and head were mapped to 13 linkage groups (GGA1, 2, 3, 4, 5, 7, 8, 9, 11, 12, 14, 18 and 27). Under the paternal half-sib model, six genome-wide significant QTL and 18 suggestive linkages for percentages of carcass parts, shank and head were detected on nine chicken linkage groups (GGA1, 2, 3, 4, 5, 12, 14, 15 and 27), seven of which seemed to corroborate positions revealed by the previous model. Overall, three novel QTL of importance to the broiler industry were mapped (one significant for shank% on GGA3 and two suggestive for carcass and breast percentages on GGA14 and drums and thighs percentage on GGA15). One novel QTL for wings% was mapped to GGA3, six novel QTL (GGA1, 3, 7, 8, 9 and 27) and suggestive linkages (GGA2, 4, and 5) were mapped for head%, and suggestive linkages were identified for back% on GGA2, 11 and 12. In addition, many of the QTL mapped in this study confirmed QTL previously reported in other populations.

Quantitative trait loci associated with fatness in a broiler-layer cross.

An F(2) population established by crossing a broiler male line and a layer line was used to map quantitative trait loci (QTL) affecting abdominal fat weight, abdominal fat percentage and serum cholesterol and triglyceride concentrations. Two genetic models, the line-cross and the half-sib, were applied in the QTL analysis, both using the regression interval method. Three significant QTL and four suggestive QTL were mapped in the line-cross analysis and four significant and four suggestive QTL were mapped in the half-sib analysis. A total of five QTL were mapped for abdominal fat weight, six for abdominal fat percentage and four for triglyceride concentration in both analyses. New QTL associated with serum triglyceride concentration were mapped on GGA5, GGA23 and GG27. QTL mapped between markers LEI0029 and ADL0371 on GGA3 for abdominal fat percentage and abdominal fat weight and a suggestive QTL on GGA12 for abdominal fat percentage showed significant parent-of-origin effects. Some QTL mapped here match QTL regions mapped in previous studies using different populations, suggesting good candidate regions for fine-mapping and candidate gene searches.

Initiation and elongation steps of mRNA translation are involved in the increase in milk protein yield caused by growth hormone administration during lactation.

The underlying molecular mechanisms that control milk yield and milk protein yield in domestic animals are not completely understood. In this study, the galactopoietic response to exogenous growth hormone (GH) was used as an experimental model to investigate the role of translation initiation and elongation in the regulation of milk protein synthesis in the mammary gland. A slow-release formula of commercially available GH was administered via a single subcutaneous injection to 4 lactating cows (GH group). A further 4 cows were given a single subcutaneous injection of saline (control group). Changes in mRNA transcript level and protein phosphorylation status of key members of the mammalian target of rapamycin (mTOR) pathway were assessed in mammary gland tissues of these animals using quantitative real-time PCR and Western blotting. The GH treatment enhanced the phosphorylation of ribosomal protein S6 and increased the protein abundance of eukaryotic initiation factor 4E (eIF4E) and eukaryotic elongation factor 2 (eEF2) proteins in the mammary gland of GH-treated animals. These results indicate a link between milk protein synthesis and the regulation of mRNA translation. The GH treatment did not change mRNA abundance of ribosomal protein S6, eIF4E, and eEF2, nor did it change the mRNA (mTOR, eEF2 kinase) or protein abundance of eEF2 kinase. These results demonstrate that GH administration changes mRNA translation initiation and elongation possibly via the mTOR pathway (suggested by the increased levels of ribosomal protein S6 phosphorylation), indicating that the mTOR pathway might be a potential control point in the regulation of milk protein synthesis in the mammary gland.

Multidrug resistance gene deficient (mdr1a-/-) mice have an altered caecal microbiota that precedes the onset of intestinal inflammation.

AIM: To compare caecal microbiota from mdr1a(-/-) and wild type (FVB) mice to identify differences in the bacterial community that could influence the intestinal inflammation. METHODS AND RESULTS: Caecal microbiota of mdr1a(-/-) and FVB mice were evaluated at 12 and 25 weeks of age using denaturing gradient gel electrophoresis (DGGE) and quantitative real-time PCR. DGGE fingerprints of FVB and mdr1a(-/-) mice (with no intestinal inflammation) at 12 weeks revealed differences in the presence of DNA fragments identified as Bacteroides fragilis, B. thetaiotaomicron, B. vulgatus and an uncultured alphaproteobacterium. Escherichia coli and Acinetobacter sp. were only identified in DGGE profiles of mdr1a(-/-) mice at 25 weeks (with severe intestinal inflammation), which also had a lower number of total bacteria in the caecum compared with FVB mice at same age. CONCLUSIONS: Differences found in the caecal microbiota of FVB and mdr1a(-/-) mice (12 weeks) suggest that the lack of Abcb1 transporters in intestinal cells due to the disruption of the mdr1a gene might lead to changes in the caecal microbiota. The altered microbiota along with the genetic defect could contribute to the development of intestinal inflammation in mdr1a(-/-) mice. SIGNIFICANCE AND IMPACT OF THE STUDY: Differences in caecal microbiota of mdr1a(-/-) and FVB mice (12 weeks) suggest genotype specific colonization. The results provide evidence that Abcb1 transporters may regulate host interactions with commensal bacteria. Future work is needed to identify the mechanisms involved in this possible cross-talk between the host intestinal cells and microbiota.

Quantitative trait loci for performance traits in a broiler x layer cross.

An F(2) resource population, derived from a broiler x layer cross, was used to map quantitative trait loci (QTL) for body weights at days 1, 35 and 41, weight gain, feed intake, feed efficiency from 35 to 41 days and intestinal length. Up to 577 F(2) chickens were genotyped with 103 genetic markers covering 21 linkage groups. A preliminary QTL mapping report using this same population focused exclusively on GGA1. Regression methods were applied to line-cross and half-sib models for QTL interval mapping. Under the line-cross model, eight QTL were detected for body weight at 35 days (GGA2, 3 and 4), body weight at 41 days (GGA2, 3, 4 and 10) and intestine length (GGA4). Under the half-sib model, using sire as common parent, five QTL were detected for body weight at day 1 (GGA3 and 18), body weight at 35 days (GGA2 and 3) and body weight at 41 days (GGA3). When dam was used as common parent, seven QTL were mapped for body weight at day 1 (GGA2), body weight at day 35 (GGA2, 3 and 4) and body weight at day 41 (GGA2, 3 and 4). Growth differences in chicken lines appear to be controlled by a chronological change in a limited number of chromosomal regions.

Mapping QTLs on chicken chromosome 1 for performance and carcass traits in a broiler x layer cross.

With the objective of mapping quantitative trait loci (QTLs) for performance and carcass traits, an F2 chicken population was developed by crossing broiler and layer lines. A total of 2063 F2 chicks in 21 full-sib families were reared as broilers and slaughtered at 42 days of age. Seventeen performance and carcass traits were measured. Parental F(0) and F1 individuals were genotyped with 80 microsatellites from chicken chromosome 1 to select informative markers. Thirty-three informative markers were used for selective genotyping of F2 individuals with extreme phenotypes for body weight at 42 days of age (BW42). Based on the regions identified by selective genotyping, seven full-sib families (649 F2 chicks) were genotyped with 26 markers. Quantitative trait loci affecting body weight, feed intake, carcass weight, drums and thighs weight and abdominal fat weight were mapped to regions already identified in other populations. Quantitative trait loci for weights of gizzard, liver, lungs, heart and feet, as well as length of intestine, not previously described in the literature were mapped on chromosome 1. This F2 population can be used to identify novel QTLs and constitutes a new resource for studies of genes related to growth and carcass traits in poultry.