Prediction of Breeding Values for Dairy Cattle Using Artificial Neural Networks and Neuro-Fuzzy Systems

Developing machine learning and soft computing techniques has provided many opportunities for researchers to establish new analytical methods in different areas of science. The objective of this study is to investigate the potential of two types of intelligent learning methods, artificial neural networks and neuro-fuzzy systems, in order to estimate breeding values (EBV) of Iranian dairy cattle. Initially, the breeding values of lactating Holstein cows for milk and fat yield were estimated using conventional best linear unbiased prediction (BLUP) with an animal model. Once that was established, a multilayer perceptron was used to build ANN to predict breeding values from the performance data of selection candidates. Subsequently, fuzzy logic was used to form an NFS, a hybrid intelligent system that was implemented via a local linear model tree algorithm. For milk yield the correlations between EBV and EBV predicted by the ANN and NFS were 0.92 and 0.93, respectively. Corresponding correlations for fat yield were 0.93 and 0.93, respectively. Correlations between multitrait predictions of EBVs for milk and fat yield when predicted simultaneously by ANN were 0.93 and 0.93, respectively, whereas corresponding correlations with reference EBV for multitrait NFS were 0.94 and 0.95, respectively, for milk and fat production

Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Detailed, comprehensive, and timely reporting on population health by underlying causes of disability and premature death is crucial to understanding and responding to complex patterns of disease and injury burden over time and across age groups, sexes, and locations. The availability of disease burden estimates can promote evidence-based interventions that enable public health researchers, policy makers, and other professionals to implement strategies that can mitigate diseases. It can also facilitate more rigorous monitoring of progress towards national and international health targets, such as the Sustainable Development Goals. For three decades, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) has filled that need. A global network of collaborators contributed to the production of GBD 2021 by providing, reviewing, and analysing all available data. GBD estimates are updated routinely with additional data and refined analytical methods. GBD 2021 presents, for the first time, estimates of health loss due to the COVID-19 pandemic. Methods: The GBD 2021 disease and injury burden analysis estimated years lived with disability (YLDs), years of life lost (YLLs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries using 100 983 data sources. Data were extracted from vital registration systems, verbal autopsies, censuses, household surveys, disease-specific registries, health service contact data, and other sources. YLDs were calculated by multiplying cause-age-sex-location-year-specific prevalence of sequelae by their respective disability weights, for each disease and injury. YLLs were calculated by multiplying cause-age-sex-location-year-specific deaths by the standard life expectancy at the age that death occurred. DALYs were calculated by summing YLDs and YLLs. HALE estimates were produced using YLDs per capita and age-specific mortality rates by location, age, sex, year, and cause. 95% uncertainty intervals (UIs) were generated for all final estimates as the 2·5th and 97·5th percentiles values of 500 draws. Uncertainty was propagated at each step of the estimation process. Counts and age-standardised rates were calculated globally, for seven super-regions, 21 regions, 204 countries and territories (including 21 countries with subnational locations), and 811 subnational locations, from 1990 to 2021. Here we report data for 2010 to 2021 to highlight trends in disease burden over the past decade and through the first 2 years of the COVID-19 pandemic. Findings: Global DALYs increased from 2·63 billion (95% UI 2·44–2·85) in 2010 to 2·88 billion (2·64–3·15) in 2021 for all causes combined. Much of this increase in the number of DALYs was due to population growth and ageing, as indicated by a decrease in global age-standardised all-cause DALY rates of 14·2% (95% UI 10·7–17·3) between 2010 and 2019. Notably, however, this decrease in rates reversed during the first 2 years of the COVID-19 pandemic, with increases in global age-standardised all-cause DALY rates since 2019 of 4·1% (1·8–6·3) in 2020 and 7·2% (4·7–10·0) in 2021. In 2021, COVID-19 was the leading cause of DALYs globally (212·0 million [198·0–234·5] DALYs), followed by ischaemic heart disease (188·3 million [176·7–198·3]), neonatal disorders (186·3 million [162·3–214·9]), and stroke (160·4 million [148·0–171·7]). However, notable health gains were seen among other leading communicable, maternal, neonatal, and nutritional (CMNN) diseases. Globally between 2010 and 2021, the age-standardised DALY rates for HIV/AIDS decreased by 47·8% (43·3–51·7) and for diarrhoeal diseases decreased by 47·0% (39·9–52·9). Non-communicable diseases contributed 1·73 billion (95% UI 1·54–1·94) DALYs in 2021, with a decrease in age-standardised DALY rates since 2010 of 6·4% (95% UI 3·5–9·5). Between 2010 and 2021, among the 25 leading Level 3 causes, age-standardised DALY rates increased most substantially for anxiety disorders (16·7% [14·0–19·8]), depressive disorders (16·4% [11·9–21·3]), and diabetes (14·0% [10·0–17·4]). Age-standardised DALY rates due to injuries decreased globally by 24·0% (20·7–27·2) between 2010 and 2021, although improvements were not uniform across locations, ages, and sexes. Globally, HALE at birth improved slightly, from 61·3 years (58·6–63·6) in 2010 to 62·2 years (59·4–64·7) in 2021. However, despite this overall increase, HALE decreased by 2·2% (1·6–2·9) between 2019 and 2021. Interpretation: Putting the COVID-19 pandemic in the context of a mutually exclusive and collectively exhaustive list of causes of health loss is crucial to understanding its impact and ensuring that health funding and policy address needs at both local and global levels through cost-effective and evidence-based interventions. A global epidemiological transition remains underway. Our findings suggest that prioritising non-communicable disease prevention and treatment policies, as well as strengthening health systems, continues to be crucially important. The progress on reducing the burden of CMNN diseases must not stall; although global trends are improving, the burden of CMNN diseases remains unacceptably high. Evidence-based interventions will help save the lives of young children and mothers and improve the overall health and economic conditions of societies across the world. Governments and multilateral organisations should prioritise pandemic preparedness planning alongside efforts to reduce the burden of diseases and injuries that will strain resources in the coming decades. Funding: Bill & Melinda Gates Foundation

Genomic comparisons of Persian Kurdish, Persian Arabian and American Thoroughbred horse populations

The present research aimed to characterize the Persian Kurdish horse population relative to the Persian Arabian and American Thoroughbred populations using genome-wide SNP data. Fifty-eight Kurdish, 38 Persian Arabian and 83 Thoroughbred horses were genotyped across 670,796 markers. After quality control and pruning to eliminate linkage disequilibrium between loci which resulted in 13,554 SNPs in 52 Kurdish, 24 Persian Arabian and 58 Thoroughbred horses, the Kurdish horses were generally distinguished from the Persian Arabian samples by Principal Component Analyses, cluster analyses and calculation of pairwise FST. Both Persian breeds were discriminated from the Thoroughbred. Pairwise FST between the two Persian samples (0.013) was significantly greater than zero and several fold less than those found between the Thoroughbred and Kurdish (0.052) or Thoroughbred and Persian Arabian (0.057). Cluster analysis assuming three genetic clusters assigned the Kurdish horse and Thoroughbred to distinct clusters (0.942 in cluster 2 and 0.953 in cluster 3 respectively); the Persian Arabian was not in a distinct cluster (0.519 in cluster 1), demonstrating shared ancestry or recent admixture with the Kurdish breed. Diversity as quantified by expected heterozygosity was the highest in the Kurdish horse (0.342), followed by the Persian Arabian (0.328) and the Thoroughbred (0.326). Analysis of Molecular Variance showed that 4.47% of the genetic variation was present among populations (PIS) were not significantly different from zero in any of the populations. Analysis of individual inbreeding based on runs of homozygosity using a larger SNP set suggested greater diversity in both the Kurdish and Persian Arabian than in the Thoroughbred. These results have implications for developing conservation strategies to achieve sound breeding goals while maintaining genetic diversity

Estimation of genetic parameters for body weight and egg production traits in Mazandaran native chicken

Native chicken breeding station of Mazandaran was established in 1988 with two main objectives: genetic improvement through selection programs and dissemination of indigenous Mazandarani birds. (Co)variance components and genetic parameters for economically important traits were estimated using (bi) univariate animal models with ASREML procedure in Mazandarani native chicken. The data were from 18 generations of selection (1988-2009). Heritability estimates for body weight at different ages [at hatch (bw1), 8 (bw8), 12 (bw12) weeks of ages and sex maturation (wsm)] ranged from 0.24 +/- 0.00 to 0.47 +/- 0.01. Heritability for reproductive traits including age at sex maturation (asm); egg number (en); weight of first egg (ew1); average egg weight at 28 (ew28), 30 (ew30), and 32 (ew32) weeks of age; their averages (av); average egg weight for the first 12 weeks of production (ew12); egg mass (em); and egg intensity (eint) varied from 0.16 +/- 0.01 to 0.43 +/- 0.01. Generally, the magnitudes of heritability for the investigated traits were moderate. However, egg production traits showed smaller heritability compared with growth traits. Genetic correlations among egg weight at different ages were mostly higher than 0.8. On the one hand, body weight at different ages showed positive and relatively moderate genetic correlations with egg weight traits (ew1, ew28, ew30, ew32, ew12, and av) and varied from 0.30 +/- 0.03 to 0.59 +/- 0.02. On the other hand, low negative genetic correlations were obtained between body weight traits (bw1, bw8, bw12, and wsm) and egg number (en). Also, there is low negative genetic correlation (-24 +/- 0.04 to -29 +/- 0.05) between egg number and egg weight. Therefore, during simultaneous selection process for both growth and egg production traits, probable reduction in egg production due to low reduction in egg number may be compensated by increases in egg weight

Prognostic correlation of NOTCH1 and SF3B1 mutations with chromosomal abnormalities in chronic lymphocytic leukemia patients

Abstract Background and Aim Chronic lymphocytic leukemia (CLL) is a monoclonal malignancy of B lymphocytes. Since common mutations in NOTCH1 and SF3B1, along with other possible chromosomal alterations, change disease severity and survival of patients with CLL, we aimed to evaluate the correlation of common mutations in NOTCH1 and SF3B1 as the poor prognostic markers with chromosomal abnormalities and clinical hematology. Method This retrospective study was performed on the peripheral blood of 51 patients diagnosed before chemotherapy with CLL. G‐banding karyotype and FISH were performed. For NOTCH1, exon 34 and for SF3B1, exons 14,15,16 were assessed using Sanger sequencing. Results The mutation frequency of NOTCH1 and SF3B1 with the pathogenic clinical status was 6:51 (11.76%), and variants obtained from both genes were 9:51 (17.64%). The frequency of SF3B1 mutation (K666E) was higher than in previous studies (p‐value <.05). There was a significant correlation between NOTCH1 mutations and del17p13 (p‐value = .068), also SF3B1 mutations with del11q22 (p‐value = .095) and del13q14 (p‐value = .066). Up to 90% of the specific stimuli used for the G‐banding karyotype successfully identified the malignant clone. There was a significant relationship between the cluster of differentiation 38 (CD38) expression level and NOTCH1 mutations (p‐value = .019) and a significant correlation between Binet classification and the SF3B1 (p‐value = .096). Conclusion The correlation of NOTCH1 and SF3B1 mutations with chromosomal abnormalities and CD38 expression may reveal the overall patient's survival rate. The mutations may be effective in the clonal expansion and progression of CLL, particularly in the diagnosis stage, as well as the control and management of the treatment

Comparison of multiple-trait genetic evaluation accuracy using region marker relationships with traditional best linear unbiased prediction (BLUP)

Accuracy of multiple-trait genetic evaluation based on allelic relationships with traditional best linear unbiased prediction (BLUP) was compared through computer simulation. Firstly, a base population (N = 100) was simulated; the population was half male/half female. After  reaching linkage disequilibrium between marker and QTL, phenotypic and genotypic records were simulated for the last generation. For each  animal in the base population, three chromosomes (each one Morgan in  length) was created; on each chromosome, 200 markers and 50 QTLs were randomly located. Mutation rate in each generation was 2.5 × 10-5. Total allelic relationships consider variety of genetic relationships  among relatives and employ information of non-relatives as well. In  evaluation using total allelic relationships, three separate allelic matrixes were required. To form such matrixes, firstly, marker effects were estimated for each trait using mixed model of BLUP. Then, based on these effects, particular markers of each trait as well as common  markers among two traits were determined and used to form allelic  relationship matrixes. Correlation between actual and estimated  breeding values in the last generation was evaluated based on 10 iterations. Statistical comparison was performed using t-student test. A significant difference was observed between evaluation accuracy of  studied two methods.Keywords: Marker, allelic relationships, multiple-trait evaluatio

Genomic comparisons of Persian Kurdish, Persian Arabian and American Thoroughbred horse populations.

The present research aimed to characterize the Persian Kurdish horse population relative to the Persian Arabian and American Thoroughbred populations using genome-wide SNP data. Fifty-eight Kurdish, 38 Persian Arabian and 83 Thoroughbred horses were genotyped across 670,796 markers. After quality control and pruning to eliminate linkage disequilibrium between loci which resulted in 13,554 SNPs in 52 Kurdish, 24 Persian Arabian and 58 Thoroughbred horses, the Kurdish horses were generally distinguished from the Persian Arabian samples by Principal Component Analyses, cluster analyses and calculation of pairwise FST. Both Persian breeds were discriminated from the Thoroughbred. Pairwise FST between the two Persian samples (0.013) was significantly greater than zero and several fold less than those found between the Thoroughbred and Kurdish (0.052) or Thoroughbred and Persian Arabian (0.057). Cluster analysis assuming three genetic clusters assigned the Kurdish horse and Thoroughbred to distinct clusters (0.942 in cluster 2 and 0.953 in cluster 3 respectively); the Persian Arabian was not in a distinct cluster (0.519 in cluster 1), demonstrating shared ancestry or recent admixture with the Kurdish breed. Diversity as quantified by expected heterozygosity was the highest in the Kurdish horse (0.342), followed by the Persian Arabian (0.328) and the Thoroughbred (0.326). Analysis of Molecular Variance showed that 4.47% of the genetic variation was present among populations (P<0.001). Population-specific inbreeding indices (FIS) were not significantly different from zero in any of the populations. Analysis of individual inbreeding based on runs of homozygosity using a larger SNP set suggested greater diversity in both the Kurdish and Persian Arabian than in the Thoroughbred. These results have implications for developing conservation strategies to achieve sound breeding goals while maintaining genetic diversity

Prediction of Breeding Values for Dairy Cattle Using Artificial Neural Networks and Neuro-Fuzzy Systems

Developing machine learning and soft computing techniques has provided many opportunities for researchers to establish new analytical methods in different areas of science. The objective of this study is to investigate the potential of two types of intelligent learning methods, artificial neural networks and neuro-fuzzy systems, in order to estimate breeding values (EBV) of Iranian dairy cattle. Initially, the breeding values of lactating Holstein cows for milk and fat yield were estimated using conventional best linear unbiased prediction (BLUP) with an animal model. Once that was established, a multilayer perceptron was used to build ANN to predict breeding values from the performance data of selection candidates. Subsequently, fuzzy logic was used to form an NFS, a hybrid intelligent system that was implemented via a local linear model tree algorithm. For milk yield the correlations between EBV and EBV predicted by the ANN and NFS were 0.92 and 0.93, respectively. Corresponding correlations for fat yield were 0.93 and 0.93, respectively. Correlations between multitrait predictions of EBVs for milk and fat yield when predicted simultaneously by ANN were 0.93 and 0.93, respectively, whereas corresponding correlations with reference EBV for multitrait NFS were 0.94 and 0.95, respectively, for milk and fat production

Genome-Wide Association Studies Identify Candidate Genes for Coat Color and Mohair Traits in the Iranian Markhoz Goat

The Markhoz goat provides an opportunity to study the genetics underlying coat color and mohair traits of an Angora type goat using genome-wide association studies (GWAS). This indigenous Iranian breed is valued for its quality mohair used in ceremonial garments and has the distinction of exhibiting an array of coat colors including black, brown, and white. Here, we performed 16 GWAS for different fleece (mohair) traits and coat color in 228 Markhoz goats sampled from the Markhoz Goat Research Station in Sanandaj, Kurdistan province, located in western Iran using the Illumina Caprine 50K beadchip. The Efficient Mixed Model Linear analysis was used to identify genomic regions with potential candidate genes contributing to coat color and mohair characteristics while correcting for population structure. Significant associations to coat color were found within or near the ASIP, ITCH, AHCY, and RALY genes on chromosome 13 for black and brown coat color and the KIT and PDGFRA genes on chromosome 6 for white coat color. Individual mohair traits were analyzed for genetic association along with principal components that allowed for a broader perspective of combined traits reflecting overall mohair quality and volume. A multitude of markers demonstrated significant association to mohair traits highlighting potential candidate genes of POU1F1 on chromosome 1 for mohair quality, MREG on chromosome 2 for mohair volume, DUOX1 on chromosome 10 for yearling fleece weight, and ADGRV1 on chromosome 7 for grease percentage. Variation in allele frequencies and haplotypes were identified for coat color and differentiated common markers associated with both brown and black coat color. This demonstrates the potential for genetic markers to be used in future breeding programs to improve selection for coat color and mohair traits. Putative candidate genes, both novel and previously identified in other species or breeds, require further investigation to confirm phenotypic causality and potential epistatic relationships

Image_1.TIF

<p>The Markhoz goat provides an opportunity to study the genetics underlying coat color and mohair traits of an Angora type goat using genome-wide association studies (GWAS). This indigenous Iranian breed is valued for its quality mohair used in ceremonial garments and has the distinction of exhibiting an array of coat colors including black, brown, and white. Here, we performed 16 GWAS for different fleece (mohair) traits and coat color in 228 Markhoz goats sampled from the Markhoz Goat Research Station in Sanandaj, Kurdistan province, located in western Iran using the Illumina Caprine 50K beadchip. The Efficient Mixed Model Linear analysis was used to identify genomic regions with potential candidate genes contributing to coat color and mohair characteristics while correcting for population structure. Significant associations to coat color were found within or near the ASIP, ITCH, AHCY, and RALY genes on chromosome 13 for black and brown coat color and the KIT and PDGFRA genes on chromosome 6 for white coat color. Individual mohair traits were analyzed for genetic association along with principal components that allowed for a broader perspective of combined traits reflecting overall mohair quality and volume. A multitude of markers demonstrated significant association to mohair traits highlighting potential candidate genes of POU1F1 on chromosome 1 for mohair quality, MREG on chromosome 2 for mohair volume, DUOX1 on chromosome 10 for yearling fleece weight, and ADGRV1 on chromosome 7 for grease percentage. Variation in allele frequencies and haplotypes were identified for coat color and differentiated common markers associated with both brown and black coat color. This demonstrates the potential for genetic markers to be used in future breeding programs to improve selection for coat color and mohair traits. Putative candidate genes, both novel and previously identified in other species or breeds, require further investigation to confirm phenotypic causality and potential epistatic relationships.</p