Natural hair colour within European populations is a complex genetic trait. Previous work has established that MC1R variants are the principal genetic cause of red hair colour, but with variable penetrance. Here, we have extensively mapped the genes responsible for hair colour in the white, British ancestry, participants in UK Biobank. MC1R only explains 73% of the SNP heritability for red hair in UK Biobank, and in fact most individuals with two MC1R variants have blonde or light brown hair. We identify other genes contributing to red hair, the combined effect of which accounts for ~90% of the SNP heritability. Blonde hair is associated with over 200 genetic variants and we find a continuum from black through dark and light brown to blonde and account for 73% of the SNP heritability of blonde hair. Many of the associated genes are involved in hair growth or texture, emphasising the cellular connections between keratinocytes and melanocytes in the determination of hair colour. These data contain GWAS summary statistics for hair colour of unrelated white British using UK Biobank data: GWAS red hair; GWAS blonde hair; GWAS brown hair.

Table S1. Exome sequence data sets from the HapMap. Legend: Exome sequencing of (CEU) Utah residents with ancestry from Northern and Western Europe and of (CHB) Han Chinese in Beijing, China - CEPH – HapMap. Table S2. Coverage: Reads mapped per drDCM subject. Legend: Percentage and number of reads mapped before and after filtering for each subject in the drDCM case control study. Table S3. Alignment Summary (Italian). Legend: Mean coverage: the total number of targeted bases divided by the targeted region size. Target coverage at 1X: Percentage targets with coverage greater. Table S4. Alignment summary (Chinese). Legend: Mean coverage: the total number of targeted bases divided by the targeted region size. Target coverage at 1X: Percentage targets with coverage greater. Table S5. Alignment summary: HapMap project data set. Legend: Mean coverage: the total number of targeted bases divided by the targeted region size. Target coverage at 1X: Percentage targets with coverage greater than 1X. Target coverage at 10X: Percentage targets with coverage greater than 10X. Target coverage at 20X: Percentage targets with coverage greater than 20X. Target coverage at 50X: Percentage targets with coverage greater than 50X. Table S6. drDCM 131 variants in differentially expressed genes. Table S7. drDCM Pathways. Table S8. Variants found in a pathway. Table S9. RNA-Seq drDCM genotypes: ECHS1, DBT, and MCCC1. Legend: Ref: reference allele, Alt: alternative allele, DCM: dilated cardiomyopathy, CTR: control. ECHS1: enoyl-CoA hydratase, short chain, 1, mitochondrial, DBT: Dihydrolipoamide branched chain transacylase E2, and MCCC1: methyl crotonoyl-CoA carboxylase 1. Table S10. Variants in DCM pedigrees from Italy and China. Legend: Genotypes for DCM cases for the ECHS1, DBT, and MCCC1 genes. ECHS1: enoyl-CoA hydratase, short chain, 1, mitochondrial, DBT: Dihydrolipoamide branched chain transacylase E2, and MCCC1: methyl crotonoyl-CoA carboxylase 1. Table S11. Variant scanning in HapMap data set. Legend: Control genotypes for the ECHS1, DBT, and MCCC1 genes. ECHS1: enoyl-CoA hydratase, short chain, 1, mitochondrial, DBT: Dihydrolipoamide branched chain transacylase E2, and MCCC1: methyl crotonoyl-CoA carboxylase 1. Table S12. Population Genetics for the ECHS1:rs10466126 Putative Mutation. Legend: Population Code: “CHB: Han Chinese in Beijing, China, JPT:Japanese in Tokyo, Japan, CHS: Southern Han Chinese, CDX: Chinese Dai in Xishuangbanna, China, KHV: Kinh in Ho Chi Minh City, Vietnam, CEU: Utah Residents (CEPH) with Northern and Western European Ancestry, TSI: Toscani in Italia, FIN: Finnish in Finland, GBR: British in England and Scotland, IBS: Iberian Population in Spain, YRI: Yoruba in Ibadan, Nigeria, LWK: Luhya in Webuye, Kenya, GWD: Gambian in Western Divisions in the Gambia, MSL: Mende in Sierra Leone, ESN: Esan in Nigeria, ASW: Americans of African Ancestry in SW USA, ACB: African Caribbeans in Barbados, MXL: Mexican Ancestry from Los Angeles USA, PUR: Puerto Ricans from Puerto Rico, CLM: Colombians from Medellin, Colombia, PEL: Peruvians from Lima, Peru, GIH: Gujarati Indian from Houston, Texas, PJL: Punjabi from Lahore, Pakistan, BEB: Bengali from Bangladesh, STU: Sri Lankan Tamil from the UK, ITU: Indian Telugu from the UK.” (< http://www.internationalgenome.org/category/population/> ). Table S13. Novel ECHS1 c.41insT. Table S14. drDCM differentially expressed genes. Table S15. drDCM Diseases and Functions. Table S16. ECHS1:rs10466126 and ECHS1:rs1049951 pairwise linkage disequilibrium in 24 populations from the 1000 genomes project. Table S17. Data mining: IPA knowledge database, PALLD. Table S18. Chemicals that interact with the ECHS1 gene. Table S19. The effect of chemical interactions on the expression of the ECHS1 gene. Table S20. Chemicals associated with diseases that interfere with the ECHS1 gene. (XLSX 632 kb)

Table S1. Exome sequence data sets from the HapMap. Legend: Exome sequencing of (CEU) Utah residents with ancestry from Northern and Western Europe and of (CHB) Han Chinese in Beijing, China - CEPH – HapMap. Table S2. Coverage: Reads mapped per drDCM subject. Legend: Percentage and number of reads mapped before and after filtering for each subject in the drDCM case control study. Table S3. Alignment Summary (Italian). Legend: Mean coverage: the total number of targeted bases divided by the targeted region size. Target coverage at 1X: Percentage targets with coverage greater. Table S4. Alignment summary (Chinese). Legend: Mean coverage: the total number of targeted bases divided by the targeted region size. Target coverage at 1X: Percentage targets with coverage greater. Table S5. Alignment summary: HapMap project data set. Legend: Mean coverage: the total number of targeted bases divided by the targeted region size. Target coverage at 1X: Percentage targets with coverage greater than 1X. Target coverage at 10X: Percentage targets with coverage greater than 10X. Target coverage at 20X: Percentage targets with coverage greater than 20X. Target coverage at 50X: Percentage targets with coverage greater than 50X. Table S6. drDCM 131 variants in differentially expressed genes. Table S7. drDCM Pathways. Table S8. Variants found in a pathway. Table S9. RNA-Seq drDCM genotypes: ECHS1, DBT, and MCCC1. Legend: Ref: reference allele, Alt: alternative allele, DCM: dilated cardiomyopathy, CTR: control. ECHS1: enoyl-CoA hydratase, short chain, 1, mitochondrial, DBT: Dihydrolipoamide branched chain transacylase E2, and MCCC1: methyl crotonoyl-CoA carboxylase 1. Table S10. Variants in DCM pedigrees from Italy and China. Legend: Genotypes for DCM cases for the ECHS1, DBT, and MCCC1 genes. ECHS1: enoyl-CoA hydratase, short chain, 1, mitochondrial, DBT: Dihydrolipoamide branched chain transacylase E2, and MCCC1: methyl crotonoyl-CoA carboxylase 1. Table S11. Variant scanning in HapMap data set. Legend: Control genotypes for the ECHS1, DBT, and MCCC1 genes. ECHS1: enoyl-CoA hydratase, short chain, 1, mitochondrial, DBT: Dihydrolipoamide branched chain transacylase E2, and MCCC1: methyl crotonoyl-CoA carboxylase 1. Table S12. Population Genetics for the ECHS1:rs10466126 Putative Mutation. Legend: Population Code: “CHB: Han Chinese in Beijing, China, JPT:Japanese in Tokyo, Japan, CHS: Southern Han Chinese, CDX: Chinese Dai in Xishuangbanna, China, KHV: Kinh in Ho Chi Minh City, Vietnam, CEU: Utah Residents (CEPH) with Northern and Western European Ancestry, TSI: Toscani in Italia, FIN: Finnish in Finland, GBR: British in England and Scotland, IBS: Iberian Population in Spain, YRI: Yoruba in Ibadan, Nigeria, LWK: Luhya in Webuye, Kenya, GWD: Gambian in Western Divisions in the Gambia, MSL: Mende in Sierra Leone, ESN: Esan in Nigeria, ASW: Americans of African Ancestry in SW USA, ACB: African Caribbeans in Barbados, MXL: Mexican Ancestry from Los Angeles USA, PUR: Puerto Ricans from Puerto Rico, CLM: Colombians from Medellin, Colombia, PEL: Peruvians from Lima, Peru, GIH: Gujarati Indian from Houston, Texas, PJL: Punjabi from Lahore, Pakistan, BEB: Bengali from Bangladesh, STU: Sri Lankan Tamil from the UK, ITU: Indian Telugu from the UK.” (< http://www.internationalgenome.org/category/population/> ). Table S13. Novel ECHS1 c.41insT. Table S14. drDCM differentially expressed genes. Table S15. drDCM Diseases and Functions. Table S16. ECHS1:rs10466126 and ECHS1:rs1049951 pairwise linkage disequilibrium in 24 populations from the 1000 genomes project. Table S17. Data mining: IPA knowledge database, PALLD. Table S18. Chemicals that interact with the ECHS1 gene. Table S19. The effect of chemical interactions on the expression of the ECHS1 gene. Table S20. Chemicals associated with diseases that interfere with the ECHS1 gene. (XLSX 632 kb)

There is growing appreciation of the importance of understanding the student perspective in Higher Education (HE) at both institutional and international levels. This is particularly important in Science, Technology, Engineering and Mathematics subjects such as Computer Science (CS) and Engineering in which industry needs are high but so are student dropout rates. An important factor to consider is the management of students’ initial expectations of university study and career. This paper reports on a study of CS first-year students’ expectations across three European countries using qualitative data from student surveys and essays. Expectation is examined from both short-term (topics to be studied) and long-term (career goals) perspectives. Tackling these issues will help paint a picture of computing education through students’ eyes and explore their vision of its and their role in society. It will also help educators prepare students more effectively for university study and to improve the student experience.

There is growing appreciation of the importance of understanding the student perspective in Higher Education (HE) at both institutional and international levels. This is particularly important in Science, Technology, Engineering and Mathematics subjects such as Computer Science (CS) and Engineering in which industry needs are high but so are student dropout rates. An important factor to consider is the management of students’ initial expectations of university study and career. This paper reports on a study of CS first-year students’ expectations across three European countries using qualitative data from student surveys and essays. Expectation is examined from both short-term (topics to be studied) and long-term (career goals) perspectives. Tackling these issues will help paint a picture of computing education through students’ eyes and explore their vision of its and their role in society. It will also help educators prepare students more effectively for university study and to improve the student experience.

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Story collected by Paddy Morgan, a student at Cill Cruain (B) school (Ballyglass South, Co. Galway) from informant Michael Morgan.

Story collected by Paddy Morgan, a student at Cill Cruain (B) school (Ballyglass South, Co. Galway) from informant Michael Morgan.