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  • Research Article
  • Open Access

Analysis of a large dataset reveals haplotypes carrying putatively recessive lethal and semi-lethal alleles with pleiotropic effects on economically important traits in beef cattle

  • 1,
  • 2,
  • 2,
  • 2,
  • 1, 3,
  • 1 and
  • 1Email author
Genetics Selection Evolution201951:9

https://doi.org/10.1186/s12711-019-0452-z

  • Received: 15 September 2018
  • Accepted: 21 February 2019
  • Published:

Abstract

Background

In livestock, deleterious recessive alleles can result in reduced economic performance of homozygous individuals in multiple ways, e.g. early embryonic death, death soon after birth, or semi-lethality with incomplete penetrance causing reduced viability. While death is an easy phenotype to score, reduced viability is not as easy to identify. However, it can sometimes be observed as reduced conception rates, longer calving intervals, or lower survival for live born animals.

Methods

In this paper, we searched for haplotypes that carry putatively recessive lethal or semi-lethal alleles in 132,725 genotyped Irish beef cattle from five breeds: Aberdeen Angus, Charolais, Hereford, Limousin, and Simmental. We phased the genotypes in sliding windows along the genome and used five tests to identify haplotypes with absence of or reduced homozygosity. Then, we associated the identified haplotypes with 44,351 insemination records that indicated early embryonic death, and postnatal survival records. Finally, we assessed haplotype pleiotropy by estimating substitution effects on estimates of breeding value for 15 economically important traits in beef production.

Results

We found support for one haplotype that carries a putatively recessive lethal (chromosome 16 in Simmental) and two haplotypes that carry semi-lethal alleles (chromosome 14 in Aberdeen Angus and chromosome 19 in Charolais), with population frequencies of 8.8, 15.2, and 14.4%, respectively. These three haplotypes showed pleiotropic effects on economically important traits for beef production. Their allele substitution effects are €2.30, €3.42, and €1.47 for the terminal index and €1.03, − €3.11, and − €0.88 for the replacement index, where the standard deviations for the terminal index are €22.52, €18.65, and €22.70 and for the replacement index they are €31.35, €29.82, and €35.79. We identified ZFAT as the candidate gene for semi-lethality in Aberdeen Angus, several candidate genes for the lethal Simmental haplotype, and no candidate genes for the semi-lethal Charolais haplotype.

Conclusions

We analysed genotype, reproduction, survival, and production data to detect haplotypes that carry putatively recessive lethal or semi-lethal alleles in Irish beef cattle and identified one lethal and two semi-lethal haplotypes, which have pleiotropic effects on economically important traits in beef production.

Background

Reproduction inefficiency has a major negative effect on profitability in cattle farming [14]. Over the last few decades, reproduction has deteriorated in both dairy and beef cattle in many countries, due to strong selection on production traits and their antagonistic relationship with reproduction [5, 6], and probably also to inbreeding. In recent years, this trend has begun to be readdressed in many countries by emphasising reproduction traits in animal recording and breeding goals [7, 8]. Furthermore, the advent of affordable high-density genotyping has enabled genomic selection jointly for production and reproduction traits [9, 10] and screening for recessive lethal alleles [1115].

Recessive lethal alleles are one of the genetic causes of reproduction inefficiency, because they result in embryonic death when an embryo is homozygous. They can also reduce viability of embryos and liveborn animals when their effect is not fully expressed (incomplete penetrance). Death is an easy phenotype to score but reduced viability is not as easy to identify. However, in some cases, it is observed as reduced conception rates, longer calving intervals, or lower survival for live born animals. Such alleles tend to be rare, but if their frequency increases, the number of affected (homozygous) embryos increases and so does the economic loss. Recessive lethal alleles may increase in frequency in a population because of genetic drift, linkage with favourable alleles, and heterozygote advantage. For example, a recessive lethal allele shows heterozygote advantage if it has a positive pleiotropic effect on production traits thereby conferring an advantage to heterozygous carriers, but not to affected (homozygous) embryos [16]. This would lead to the selection of heterozygous carriers as parents of the next generation, propagate the recessive lethal allele across the population, and in turn significantly affect reproduction [17].

The availability of high-density genotype data has enabled screening of livestock populations for recessive lethal alleles. There are reported successes in dairy cattle [1114], beef cattle [15], and pigs [18, 19]. The screening is based on the detection of the absence of homozygotes, either in whole populations or within carrier families. Several recessive haplotypes that show pleiotropic effects on yield, longevity and fertility in dairy cattle have been reported [20].

Recently, the Irish Cattle Breeding Federation (ICBF) has initiated large-scale genotyping of commercial beef cattle in Ireland [21]. To date, more than 1.3 million purebred and crossbred animals have been genotyped. These data will enable genomic selection to increase the productivity and reduce the environmental footprint of Irish cattle [22]. It can also be a powerful resource for biological discovery, including detection of recessive lethal or semi-lethal alleles, should they exist.

The objectives of our study were to discover haplotypes that carry putatively recessive lethal or semi-lethal alleles in the most numerous Irish beef cattle breeds, and to quantify their pleiotropic effects on traits under selection. We phased the genotypes in sliding windows along the genome for 132,725 purebred animals from five breeds and used five tests to identify haplotypes with absence or reduced homozygosity. We corroborated the identified haplotypes with reproduction and postnatal survival records. We found support for one haplotype that carries a putatively recessive lethal allele and two haplotypes that carry putatively recessive semi-lethal alleles. Substitution analysis showed that these haplotypes had pleiotropic effects on economically important traits in Irish beef cattle.

Methods

In this paper, we analysed genotype, reproduction, survival, and production data to identify and validate haplotypes that carry putatively recessive lethal or semi-lethal alleles in Irish beef cattle. Briefly, our approach consisted of:
  1. (1)

    Genotype filtering, imputation, and phasing,

     
  2. (2)

    Identification of haplotypes that carry putatively recessive lethal or semi-lethal alleles,

     
  3. (3)

    Reproduction and survival analysis to corroborate the identified haplotypes,

     
  4. (4)

    Pleiotropy analysis to estimate haplotype effects on production traits,

     
  5. (5)

    Identification of candidate genes.

     

Genotype filtering, imputation, and phasing

We used single nucleotide polymorphism (SNP) array data from the ICBF for purebred Aberdeen Angus, Charolais, Hereford, Limousin, and Simmental animals. The animals were genotyped with four different, but overlapping, Illumina SNP arrays (HD, IDBv1, IDBv2, and IDBv3; see Table 1), with most of the animals genotyped on the IDBv3 array (> 64%). We filtered the genotype data on autosomal chromosomes, missing information, and heterozygosity. We excluded SNPs with a low genotype call rate (< 0.90), and animals with a low genotype call rate (< 0.90) or high heterozygosity (> 6 standard deviations from mean heterozygosity). After filtering, 132,725 animals were available: 22,836 Aberdeen Angus; 39,472 Charolais; 12,678 Hereford; 45,965 Limousin; and 11,774 Simmental animals (Table 1). Finally, we reduced the SNPs to those that were present on the IDBv3 array and had a minor allele frequency higher than 0.05 within each breed. This decreased the number of SNPs to 40,146 for Aberdeen Angus; 41,366 for Charolais; 40,368 for Hereford; 40,951 for Limousin; and 39,907 for Simmental. We imputed missing genotypes in these reduced sets with AlphaImpute version 1.9.1 [23], and then they were phased with AlphaPhase version 1.9.1 [23] (using a core and tail length of 320 SNPs) into 20 SNP haplotypes in sliding windows. This means that the genotypes at each locus were phased 20 times in sliding windows, with the start of each window being moved along by one SNP at a time.
Table 1

Number of SNPs per array and number of genotyped animals after genotype filtering per breed and array

Number of genotyped animals per breed and array

Number of SNPs per array

Total

HD

IDBv1

IDBv2

IDBv3

774,959

16,044

16,291

53,368

Aberdeen Angus

532

1969

5409

14,926

22,836

Charolais

1,035

3950

10,868

23,619

39,472

Hereford

362

1759

2825

7,732

12,678

Limousin

1043

4134

10,717

30,071

45,965

Simmental

417

820

1798

8739

11,774

Total

3389

12632

31,617

85,087

132,725

Identification of haplotypes that carry putatively recessive lethal or semi-lethal alleles

To identify haplotypes that carry putatively recessive lethal or semi-lethal alleles, the phased haplotypes from 132,725 animals were analysed for complete absence or a reduced level of homozygosity within the analysed breed (see Table 1). We used five different tests that were grouped into three categories: (i) population, (ii) carrier mating, and (iii) semi-lethality. The first and second categories are based on the probability of observing complete absence of recessive homozygous animals in the whole population or in the progeny from carrier matings. Thus, they assume that recessive lethal alleles are completely penetrant. The third category tests the null hypothesis that observed and expected numbers of recessive homozygous animals are equal. Thus, it is able to detect recessive semi-lethal alleles, with some homozygotes not suffering from deleterious effects or some haplotypes that imperfectly tag a recessive lethal allele. From this point on, we will use HH to denote wild type homozygotes, Hh to denote heterozygotes, and hh to denote homozygotes for a haplotype that carries putatively recessive lethal alleles.

Population test

The first test identifies haplotypes that carry putatively recessive lethal alleles based on their population frequency. The probability of observing no hh animals (Phh) depends on the Hh frequency (c) and the number of genotyped animals (N): Phh= (1 − c2/4)N. The number of expected hh animals (Ehh) under these conditions is equal to: Ehh= (N/4)·c2. This test is the same as that used by VanRaden et al. [12].

Carrier mating tests

The second category consists of two tests that identify haplotypes that carry putatively recessive lethal alleles based on the expected number of hh progeny from Hh × Hh matings. We analysed both sire × dam and sire × maternal grand-sire Hh × Hh matings. The probability of observing no hh animals follows a Bernoulli process and can be calculated as Phh= 0.75C for C sire × dam Hh × Hh matings and Phh= 0.875C for C sire × maternal grand-sire Hh × Hh matings. The expected number of hh progeny was calculated as C/4 for sire × dam Hh × Hh matings and C/8 for sire × maternal grand-sire Hh × Hh matings. These tests are partially the same as that used by VanRaden et al. [12].

Semi-lethality tests

The third category tests the null hypothesis that the observed and expected number of hh animals do not differ based on sire × dam Hh × Hh or sire × maternal grand-sire Hh × Hh matings. From the number of observed and expected hh (Ohh and Ehh), Hh (OHh and EHh), and HH (OHH and EHH) progeny, we calculated a one-way Chi square test statistic: χ2 = (Ohh − Ehh)2/Ehh+ (OHH+Hh − EHH+Hh)2/EHH+Hh. The test statistic has one degree of freedom.

Identification of haplotypes that carry putative recessive lethal or semi-lethal alleles

Haplotypes that show absence or a reduced level of homozygosity at p < 5 × 10−8 (−log10p > 7.30) were considered as candidates for carrying putatively recessive lethal or semi-lethal alleles that cause early embryonic death or reduced postnatal survival. In order to decrease the false discovery rate, only 1 Mb long regions with at least nine haplotype tests with p < 5 × 10−8 were considered. From each of these regions, only the most significant haplotype test from each of the three test categories was selected. We analysed the effect of each of these haplotypes on cow reproduction and progeny survival to corroborate lethality and on production traits to evaluate pleiotropy.

Reproduction and survival analysis to corroborate the identified haplotypes

We used routine cow reproduction and progeny survival records from the ICBF database. We tracked 44,351 insemination records that pertain to purebred Aberdeen Angus, Charolais, Hereford, Limousin, or Simmental cattle, for which both the cow and the AI sire that it is mated to, were genotyped. There were 7540 records for Aberdeen Angus, 11,520 for Charolais, 5566 for Hereford, 15,404 for Limousin, and 4321 for Simmental. Altogether these inseminations resulted in 21,196 progeny. Each resulting calf had records for its date of birth and, if deceased, its date of death and the cause of death (natural death or slaughtered). All the new born calves were followed from birth until November 2017. If they were still alive at the end of data collection their records were treated as censored.

To quantify the effect of identified haplotypes on reproduction, we determined the insemination success rate based on the number of days between a recorded insemination and the subsequent calving date. Insemination success rate was calculated as a ratio between the number of born progeny and the number of inseminations. These statistics were reported for the three mating types: (1) Hh × Hh, (2) Hh × HH, and (3) HH × HH. The interval between insemination and calving was calculated from 40,769 records for which the date of the corresponding calving was known. In order to accommodate shorter or longer than average gestation length, a window of 7, 14, or 21 days was allowed on either side of the breed average gestation length, calculated as the average gestation length for the set of individuals recorded for that breed. If a calving occurred outside of the window, the insemination was deemed to be unsuccessful. If a haplotype harbours recessive lethal alleles, Hh × Hh matings are expected to have a 25% lower insemination success since there will be 25% hh progeny and an interval between insemination and calving longer than 21 days, which is the average time between each standing oestrus in cattle.

To quantify the effect of identified haplotypes on postnatal survival, we used survival analysis with the Cox proportional-hazard model. We compared hazard ratios between the progeny from: (1) Hh × Hh, (2) Hh × HH, and (3) HH × HH matings. If a haplotype affects postnatal survival, we would expect hh progeny from Hh × Hh matings to have a higher hazard ratio. Since two causes of death were reported (natural death and slaughtered), we analysed data in two ways: (1) we treated records from slaughtered animals as censored, and (2) we treated their records as uncensored.

Pleiotropy analysis

We analysed estimated breeding values to investigate pleiotropic effects of the identified haplotypes on economically important traits in beef production. Estimated breeding values for 15 traits (feed intake, live weight, cull cow weight, carcass weight, carcass confirmation, carcass fat, docility, gestation length, age at first calving, calving interval, calving difficulty due to the sire, maternal calving difficulty, mortality at calving, maternal weaning weight, and cow survival) for all genotyped individuals in this study were available from the May 2017 routine genetic evaluation carried out by the ICBF. These 15 traits are included in two indexes with different economic weights and trait emphasis (shown in parentheses). The economic weights were calculated based on the costs of inputs and the value of final products [24]. We used the same economic weights and trait emphasis as used currently by ICBF. The terminal index consists of: calving difficulty due to sire (− €4.65, 18%), gestation length (− €2.25, 4%), mortality (− €5.34, 3%), docility (€17.03, 2%), feed intake (-€0.10, 16%), carcass weight (€3.14, 41%), carcass conformation (€14.77, 11%), and carcass fat (− €7.86, 5%). The replacement index consists of eight cow traits: maternal calving difficulty (− €4.98, 6%), age at first calving (− €0.99, 6%), calving interval (− €5.07, 9%), cow survival (€8.86, 8%), maternal weaning weight (€5.58, 18%), cow live weight (− €1.31, 13%), cow docility (€77.27, 4%), cull cow weight (€0.91, 7%); and eight calf traits: calving difficulty due to sire (− €5.12, 7%), gestation length (− €2.48, 2%), mortality (− €5.87, 1%), calf docility (€14.72, 1%), feed intake (− €0.07, 4%), carcass weight (€2.10, 10%), carcass conformation (€10.22, 3%), and carcass fat (− €5.44, 1%). For every identified haplotype, we estimated its substitution effect on the estimated breeding values for each of the 15 traits and two indexes. Only estimated breeding values with at least 25% reliability on the trait of interest were used, which amounted to between 1515 and 43,963 records being used of which between 29.4 and 87.0% were from sires with progeny and between 0.8 and 92.4% were from animals with their own phenotypes. The substitution effect was estimated by linear regression of estimated breeding values on the number of haplotype copies that an animal carries. Trait-specific substitution effects were divided by the standard deviation of the estimated breeding values to present the effects on a comparable scale.

Economic impact

For the estimation of economic impact of putative lethal or semi-lethal haplotypes on the whole Irish beef population, we built a simple economic model. This model was based on the number of purebred sire × purebred dam, purebred sire × crossbred dam, and crossbred sire × crossbred dam of Aberdeen Angus, Charolais, and Simmental animals, the expected number of progeny genotypes, haplotype frequencies, insemination success rate, number of days between the subsequent inseminations, daily costs for maintaining a cow, and substitution effects. We obtained these inputs from this study, the ICBF database, and the E-profit monitor—an online financial analysis tool [25].

Candidate genes

We used Bioconductor version 3.7 with the BioMart database version Ensembl Genes 92 using the btaurus_gene_ensembl to find candidate genes within the regions of the identified haplotypes [26]. We used the UMD3.1 cattle reference genome [27]. We extracted the protein coding genes and searched for lethal effects observed with homologous genes with the same function in the Mouse Genome Informatics database [28].

Results

Our results identified one haplotype that carries a putatively recessive lethal allele and two haplotypes that carry putatively recessive semi-lethal alleles, which were located on chromosome 16 in Simmental, chromosome 14 in Aberdeen Angus, and chromosome 19 in Charolais, respectively. These haplotypes showed pleiotropic effects on economically important beef production traits. We identified the zinc finger and AT-hook domain containing (ZFAT) gene as the potential causative gene for semi-lethality in Aberdeen Angus.

Identification of haplotypes that carry putative recessive lethal or semi-lethal alleles

Haplotype tests

In total, there were between 36 and 109 haplotypes with significant absence or reduced levels of homozygosity at p < 5 × 10−8 in the five breeds. Table 2 shows the number of significant haplotypes by test and breed. The largest number of significant haplotypes was observed for Limousin (109) followed by Charolais (86), Aberdeen Angus (69), Hereford (57), and Simmental (36). Among the different tests, the semi-lethality test on sire × dam matings had the largest number of significant haplotypes. The carrier mating test on sire × dam matings had the second largest number of significant haplotypes for Charolais, Hereford, and Simmental.
Table 2

Number of haplotypes with a significant absence or reduced level of homozygosity at p < 5 × 10−8 by test and breed

Testa

Aberdeen Angus

Charolais

Hereford

Limousin

Simmental

T1

3

0

0

8

6

T2

1

9

13

14

15

T3

2

3

0

3

1

T4

65

72

56

90

16

T5

1

5

11

15

1

Totalb

69

86

57

109

36

aT1: population test; T2: carrier mating test on sire × dam matings; T3: carrier mating test on sire × maternal grand-sire matings; T4: semi-lethality test on sire × dam matings; T5: semi-lethality test on sire × maternal grand-sire matings

bTotal number of haplotypes with p < 5 × 10−8 from at least one test

Identification of haplotypes that carry putative recessive lethal or semi-lethal alleles

Across all five breeds, there were 19 one-Mb long regions with at least nine haplotypes that showed significant absence or a reduced level of homozygosity. These were considered as candidate regions with haplotypes that carry putatively recessive lethal or semi-lethal alleles. Figure 1 shows the negative logarithm of all test p-values across the whole genome and the 19 candidate regions are listed in Additional file 1: Table S1, with five regions for Aberdeen Angus, two for Charolais, three for Hereford and Limousin, and six for Simmental. Some of the regions were in close proximity and appeared as a single region (see Fig. 1). This was the case for three regions on chromosome 14 in Aberdeen Angus, two regions on chromosome 6 in Hereford, two regions on chromosome 23 in Limousin, and three regions on chromosome 13 and two regions on chromosome 16 in Simmental. The region between 48 and 49 Mb on chromosome 19 was detected in all the breeds.
Fig. 1
Fig. 1

Genome-wide Manhattan plot for lack of homozygosity in a Aberdeen Angus, b Charolais, c Hereford, d Limousin, and e Simmental breeds

From the 19 candidate regions, we selected 22 haplotypes with the highest significance within each of the three category tests. Table 3 lists the 22 haplotypes and their characteristics. We named the haplotypes by using a code including the breed (AA for Aberdeen Angus, CH for Charolais, HE for Hereford, LI for Limousin and SI for Simmental), the chromosome, and the haplotype number within the breed (H for haplotype). Except for HE19H3 and SI19H6, which were identified with tests from two categories (carrier mating test with sire × dam matings from the carrier mating tests and semi-lethality test with sire × dam matings from the semi-lethality tests), all haplotypes were identified by tests from a single category.
Table 3

Identified haplotypes carrying putatively recessive lethal or semi-lethal alleles

Haplotype name

Testa

Chrb

Haplotype region

Sliding window

Start base

End base

Haplotype percentage

AA14H1

T4

14

AA14R1

4

6,819,966

7,514,610

25.2

AA14H2

T4

14

AA14R2

9

7,646,485

8,425,401

15.3

AA14H3

T4

14

AA14R3

20

8,064,004

8,927,881

15.2

AA14H4

T3

14

AA14R3

9

8,454,690

9,215,622

15.3

AA18H5

T4

18

AA14R4

4

49,446,631

50,616,688

18.9

AA19H6

T4

19

AA14R5

8

48,850,043

48,874,999

23.9

CH13H1

T4

13

CH13R1

19

61,565,261

61,584,644

33.5

CH19H2

T4

19

CH19R2

5

48,874,999

48,902,319

14.4

CH19H3

T3

19

CH19R2

12

48,889,025

48,914,435

1.2

HE6H1

T4

6

HE6R1

8

58,473,731

59,706,074

30.2

HE6H2

T4

6

HE6R2

4

59,688,857

60,919,136

28.8

HE19H3

T2, T4

19

HE19R3

13

48,854,119

48,900,428

28.9

LI19H1

T5

19

LI19R1

20

48,851,566

48,871,260

12.7

LI19H2

T2

19

LI19R1

11

48,883,348

48,906,682

11.1

LI23H3

T4

23

LI23R2

20

27,923,154

28,649,349

13.7

LI23H4

T4

23

LI23R3

12

28,307,706

29,872,481

11.5

SI13H1

T2

13

SI13R1, SI13R2

15

73,746,516

74,973,171

9.5

SI13H2

T4

13

SI13R1, SI13R2, SI13R3

19

73,895,443

75,240,419

22.3

SI13H3

T2

13

SI13R2, SI13R3

1

74,109,992

75,310,875

9.3

SI16H4

T2

16

SI16R4, SI16R5

16

51,195,450

53,097,936

10.8

SI16H5

T1

16

SI16R4, SI16R5

4

51,811,400

53,434,159

8.8

SI19H6

T2, T4

19

SI19R6

18

48,873,060

48,891,361

18.4

aT1: population test; T2: carrier mating test on sire × dam matings; T3: carrier mating test on sire × maternal grand-sire matings; T4: semi-lethality test on sire × dam matings; T5: semi-lethality test on sire × maternal grand-sire matings

bChr: chromosome number

Reproduction and survival analysis to corroborate the identified haplotypes

Reproduction analysis

Two out of the 22 identified haplotypes, AA14H3 and SI16H5, were associated with decreased insemination success rate and a longer interval between insemination and calving. Table 4 shows the insemination success rate and the length of the interval between insemination and calving for the non-carrier × non-carrier (HH × HH), non-carrier × carrier (HH × Hh), and carrier × carrier (Hh × Hh) matings for the AA14H3 and SI16H5 haplotypes. AA14H3 was located on chromosome 14 (8,064,004–8,927,881 bp) in Aberdeen Angus and SI16A5 on chromosome 16 (51,811,400–53,434,159 bp) in Simmental. The insemination success rates for Hh × Hh matings were 24.2, 23.0, and 20.2% lower (AA14H3), and 48.6, 52.5, and 52.7% lower (SI16H5) compared to the HH × HH matings for windows of 7, 14, and 21 days on either side of the average gestation length for each breed, respectively. The insemination success rates were also lower in HH × Hh matings than in HH × HH matings, but the differences were smaller.
Table 4

Insemination success rate and interval between insemination and calving for non-carrier × non-carrier matings (HH × HH), non-carrier × carrier (HH × Hh), and carrier × carrier (Hh × Hh) matings for the AA14H3 and SI16H5 haplotypes and a calf registration window of 7, 14, and 21 days

Mating type

Window (days)

Haplotype allele

AA14H3 (8,064,004–8,927,881 bp)a

SI16H5 (51,811,400–53,434,159 bp)a

HH × HH

HH × Hh

Hh × Hh

HH × HH

HH × Hh

Hh × Hh

Number of matings

 

1005

783

154

779

492

32

Success rate (%)

7

42.9

41.3

32.5

36.6

35.0

18.8

14

54.0

51.6

41.6

46.1

44.5

21.9

21

55.4

53.9

44.2

46.3

44.7

21.9

Change in success rate against non-carrier × non-carrier matings (%)

7

 

− 3.7

− 24.2

 

− 4.4

− 48.6

14

 

− 4.4

− 23.0

 

− 3.5

− 52.5

21

 

− 2.7

− 20.2

 

− 3.5

− 52.7

Days from insemination to calving

 

319

323

349

328

337

358

aGenomic region in bp of the haplotype

For both haplotypes (AA14H3 and SI16H5) the interval between insemination and calving was longer for Hh × Hh matings than for HH × Hh matings, which was in turn longer than for HH × HH matings. The interval between insemination and calving for Hh × Hh matings was 30 days longer than for HH × HH matings for both AA14H3 and SI16H5 haplotypes, and that for HH × Hh matings was longer than for HH × HH matings by 4 days for AA14H3 and by 9 days for SI16H5.

Survival analysis

One of the identified haplotypes, CH19H2 was associated with a significantly (p < 0.05) increased hazard ratio for postnatal survival (i.e. decreased survival) of progeny from Hh × Hh matings. CH19H2 is located on chromosome 19 (48,874,999–48,902,319 bp) in Charolais. Additional file 2: Table S2 presents the hazard ratios for progeny from HH × Hh and Hh × Hh matings compared to those for progeny from HH × HH matings, for which records for culled progeny were treated as censored or complete. Progeny of individuals that carried the CH19H2 haplotype had a 36% higher probability of dying or being slaughtered during their life compared to the progeny of HH × HH parents.

Frequencies for haplotypes that carry putatively recessive lethal or semi-lethal alleles

All three haplotypes that carry putatively recessive lethal or semi-lethal alleles associated with decreased insemination success or reduced postnatal survival had high frequencies. Table 5 summarizes the statistics for the AA14A3, CH19A2, and SI16A5 haplotypes. Haplotype frequencies were 15.2% for AA14A3, 14.4% for CH19A2, and 8.8% for SI16A5. Ninety-five recessive homozygous individuals were observed for AA14A3, 83 for CH19A2, and none for SI16A5. This suggests that the SI16A5 haplotype carries a putatively recessive lethal allele, whereas AA14A3 and CH19A2 haplotypes carry putatively recessive semi-lethal alleles. Table 5 shows that the number of observed recessive homozygotes was always smaller than the expected number for different types of comparisons. SNP alleles present on the AA14A3, CH19A2, and SI16A5 haplotypes are in Additional file 3: Table S3.
Table 5

Statistics for the AA14H3, CH19H2, and SI16H5 haplotypes

Haplotype

AA14H3

CH19H2

SI16H5

Genotyped animals

22,510

38,960

11,559

Frequency (%)

15.2

14.4

8.8

Recessive homozygotes

95

83

0

Expected recessive homozygotes

194.1

256

47.6

Sire-carrier × dam-carrier matings

220

256

17

Recessive homozygotes from sire-carrier × dam-carrier matings

2

6

0

Expected recessive homozygotes from sire-carrier × dam-carrier matings

55

64

4.3

Sire-carrier × maternal grand-sire-carrier matings

141

87

7

Recessive homozygotes from sire-carrier × maternal grand-sire-carrier matings

0

1

0

Expected recessive homozygotes from sire-carrier × maternal grand-sire-carrier matings

17.6

10.9

0.9

Probability of not observing recessive homozygotes with the T1 testa

2.3 × 10−85

2.5 × 10−112

2.0 × 10−21

Probability of not observing recessive homozygotes with the T2 testa

3.3 × 10−28

1.0 × 10−32

7.9 × 10−3

Probability of not observing recessive homozygotes with the T3 testa

6.7 × 10−9

9.0 × 10−9

3.9 × 10−1

Probability that the observed and expected number of recessive homozygotes are not different with the T4 testa

1.1 × 10−16

1.1 × 10−16

1.7 × 10−2

Probability that the observed and expected number of recessive homozygotes are not different with the T5 testa

7.2 × 10−6

1.4 × 10−3

3.2 × 10−1

aT1: population test; T2: carrier mating test on sire × dam matings; T3: carrier mating test on sire × maternal grand-sire matings; T4: semi-lethality test on sire × dam matings; T5: semi-lethality test on sire × maternal grand-sire mating

Pleiotropy analysis

To investigate potential pleiotropic effects on traits under selection, we estimated the substitution effects of the AA14H3, CH19H2, and SI16H5 haplotypes. Figure 2 shows standardized substitution effects, presented in the units of a trait standard deviation, for 15 traits that are part of the terminal or replacement index. A significant substitution effect for the AA14H3 haplotype was observed for cull cow weight (0.37), followed by live weight (0.34), feed intake (0.31), calving interval (0.30), maternal calving difficulty (− 0.25), carcass weight (0.25), carcass fat (− 0.13), age at first calving (− 0.12), calving difficulty (0.10), cow survival (− 0.10), carcass conformation (− 0.07), gestation length (0.06), and maternal weaning weight (− 0.04). Collectively, one copy of the AA14H3 haplotype increased the terminal index by €3.42 where one standard deviation is €18.65, and decreases the replacement index by €3.11, where one standard deviation is €29.82. A significant substitution effect for the SI16H5 haplotype was observed for feed intake (− 0.24), followed by cow survival (0.17), cull cow weight (0.15), carcass fat (− 0.11), maternal calving difficulty (− 0.09), carcass conformation (0.09), and live weight (0.09). Collectively, one copy of the SI16H5 haplotype increased the terminal index by €2.30 where one standard deviation is €22.52 and the replacement index by €1.03 where one standard deviation is €31.35. A significant substitution effect for the CH19H2 haplotype was observed for maternal weaning weight (− 0.18), maternal calving difficulty (0.13), carcass conformation (0.12), carcass fat (− 0.11), live weight (− 0.10), feed intake (− 0.09), age at first calving (− 0.09), gestation length (0.07), calving difficulty (0.07), mortality (0.04), and carcass weight (0.04). Collectively, one copy of the CH19H2 haplotype increased the terminal index by €1.47 where one standard deviation is €22.70 and decreased the replacement index by €0.88 where one standard deviation is €35.79.
Fig. 2
Fig. 2

Standardized substitution effects with 95% confidence interval for the haplotypes a AA14H3, b SI16H5, and c CH19H2 on 15 traits. FEED_IN, feed intake; LIVE_WT, live weight; CULL_COW, cull cow weight; CARC_WT, carcass weight; CARC_CONF, carcass confirmation; CARC_FAT, carcass fat; DOC, docility; GL, gestation length; AFC, age at first calving; CIV, calving interval; CD, calving difficulty due to the sire; MCD, maternal calving difficulty; MORT, mortality at calving; MAT_WW, maternal weaning weight; COW_SURV, cow survival

Economic impact

The expected economic impact estimated with a simple economic model is presented in Additional file 4: Table S4. The annual losses due to decreased viability and decreased survival for each haplotype were estimated to reach ~ €570,000 for AA14H3, ~ €930,000 for CH19H2, and ~ €210,000 for SI16H5. The annual gains due to positive associations with economically important traits were estimated to reach ~ €110,000 for AA14H3, ~ €70,000 for CH19H2, and ~ €50,000 for SI16H5. Under the current population structure in Ireland, the estimated national annual net effects were negative: − €450,000 for AA14H3 − €860,000 for CH19H2, and − €160,000 for SI16H5. The large negative net effect of the CH19H2 haplotype is due to the larger purebred population in Charolais than in Aberdeen Angus and Simmental. The economic model shows that, under the current population structure, the maximum annual net effects would be achieved with haplotype frequencies of 0.02% for AA14H3 (+€7,000), 0.01% for CH19H2 (+€2,000), and SI16H5 (+€4,000) [see Additional file 5: Figure S1].

Candidate genes

We identified one protein coding gene in the region of AA14H3, none in the region of CH19H2, and several in the region of SI16H5. Zinc finger and AT-hook domain containing (ZFAT) is the only protein coding gene located between 8,064,004 and 8,927,881 bp on chromosome 14 of the AA14A3 haplotype. ZFAT is associated with prenatal or perinatal lethality in the Mouse Informatics Database. Additional file 6: Table S5 lists the 64 protein coding genes located between 51,811,400 and 53,434,159 bp on chromosome 16 of the SI16H5 haplotype, among which five, i.e. SKI proto-oncogene (SKI), G protein subunit beta 1 (GNB1), ATPase family AAA domain-containing protein 3 (ATAD3A), zinc finger and BTB domain containing 17 (ZBTB17), and caspase-9 (CASP9)) are associated with prenatal or perinatal lethality in mice.

Discussion

Our results reveal one haplotype that carries a putatively recessive lethal allele (SI16A5) and two haplotypes that carry putatively recessive semi-lethal alleles (AA14A3 and CH19A2) that are candidates for lethality or semi-lethality in homozygous state. These three haplotypes were identified by the haplotype analysis of 132,725 purebred animals of five beef cattle breeds from the ICBF database. The results also suggest pleiotropy, since these haplotypes include or are in strong linkage with variants that have substantial effects on economically important traits. In the light of these results, we discuss (1) the identification of haplotypes that carry putative recessive lethal and semi-lethal alleles, (2) the frequency of the identified haplotypes, (3) their economic impact, and (4) their potential genetic causes.

Identification of haplotypes that carry putative recessive lethal or semi-lethal alleles

We used five tests on sliding haplotypes and phenotypic information to search for haplotypes that carry recessive lethal or semi-lethal alleles. We used haplotypes in a sliding window of 20 SNPs, which was previously shown to be a good compromise between haplotype diversity and detection of putative recessive lethal alleles with a moderate SNP density array [15]. The tests were based on the number of expected recessive homozygous individuals either in the whole population or from matings between carriers. Along with the tests for complete absence of recessive homozygotes, we also used a set of tests that allowed for some recessive homozygotes but tested whether their number was significantly smaller than expected. This allowed us to take possible incomplete penetrance, incomplete linkage between haplotype and putative recessive lethal alleles, structural variation, or genotyping, phasing, and imputation errors into account. In the following, we consider that all are semi-lethal.

The top 22 candidates from the haplotype analysis were further corroborated with cow insemination and progeny survival analysis, and three haplotypes showed phenotypic evidence of lethality. Recessive lethal alleles are expected to decrease insemination success and extend the interval between insemination and calving. In the case of semi-lethality, some embryos are expected to survive, but these may have a decreased viability that will in turn affect their survival.

Although there were many haplotypes with a significant absence or reduced level of homozygosity, which indicated that they carried putatively recessive lethal or semi-lethal alleles, only two haplotypes were supported by the reproduction analysis. In particular, there was a strong signal observed at the end of chromosome 19 for all five cattle breeds, which was supported by phenotypic data only in the Charolais breed. A highly significant departure from Hardy–Weinberg equilibrium was observed for SNPs that were located at the end of chromosome 19 with an excessive heterozygosity level (results not shown). This may indicate genotyping errors or structural variation in this region [29] that could explain the strong signal observed.

Frequency of haplotypes that carry putatively recessive lethal or semi-lethal alleles

For our methods to detect a haplotype that carries putatively recessive lethal or semi-lethal alleles, we needed a relatively high haplotype frequency or many Hh × Hh matings. Because most haplotypes are rare, this means that the methods we used had sufficient power for a very small proportion of the haplotypes. Following the probability calculations of the different tests and fixing the number of genotyped animals to the number available for this study, we were able to assess the minimum required haplotype frequency with a significance of p < 5 × 10−8, i.e. 5.42% for Aberdeen Angus, 4.14% for Charolais, 7.29% for Hereford, 3.83% for Limousin, and 7.56% for Simmental. The percentages of haplotypes with a frequency higher than these thresholds were very low: 0.98% for Aberdeen Angus, 0.68% for Charolais, 1.01% for Hereford, 0.56% for Limousin, and 0.52% for Simmental. Similarly, reaching such significance with the carrier mating test would require at least 59 sire × dam carrier (Hh × Hh) matings and no homozygous progeny. The percentages of haplotypes reaching this threshold were even smaller than for the population test: 0.44% for Aberdeen Angus, 0.23% for Charolais, 0.37% for Hereford, 0.20% for Limousin, and 0.16% for Simmental. Furthermore, reaching significance with the carrier mating test would require 126 sire × maternal grand-sire carrier (Hh × Hh) matings and no homozygous progeny. The percentage of haplotypes reaching this threshold were even smaller than for the carrier mating test with sire × dam matings, i.e. 0.06% for Aberdeen Angus, 0.04% for Charolais and Hereford, 0.03% for Limousin, and 0.02% for Simmental. Finally, reaching significance with the semi-lethality test required that the Chi square test statistic be higher than 29.72. The percentages of haplotypes that reached this threshold in the current study was less than 0.01% for all the breeds.

Since recessive lethal and semi-lethal alleles are usually rare and breed-specific, they are difficult to detect in a population, in particular for recent mutations since modern breeding programs try to avoid inbreeding to preserve genetic variation and maintain fitness. Thus, breeders are likely to indirectly avoid carrier matings because they avoid matings between close relatives. Still, there are some alleles that are propagated through the population via popular sires, have pleiotropic effects, or are in incomplete linkage with an allele that has a positive effect on a trait that was selected for in the past. A classic example of a recessive lethal allele propagated with a popular sire is the complex vertebral malformation (CVM) of calves in the Holstein breed. The causal mutation was propagated by the bull Carlin-M Ivanhoe Bell that was incidentally also a carrier of the bovine leukocyte adhesion deficiency (BLAD) [30]. An example of a pleiotropic recessive lethal allele is a 660-kb deletion that causes embryonic death in Nordic Red cattle [14]. Since this deletion is positively associated with milk yield, it is quite common (13–32%) in the Nordic Red cattle population. Yet another example is the Weaver syndrome which is expressed postnatally between the age of 5 and 8 months [31], with Weaver-carriers also producing more milk and fat, which have been strongly selected for in the past [31, 32].

High haplotype frequencies and substitution effects on traits under selection suggest that the frequency of the detected haplotypes in this study may have increased because of pleiotropy or linked selection. The observed frequencies are high compared to expected frequencies with mutation-selection equilibrium. We can use Nei’s [33] formula to approximate the expectation and variance of the frequency of a recessive lethal allele in a finite population, where µ is the mutation rate, Ne the effective population size, and s the selection coefficient against the mutant lethal:
$$\bar{q} \approx \mu \sqrt {2 \pi \frac{{N_{e} }}{s}} \quad {\text{and}}\quad \sigma^{2} \approx \frac{\mu }{s} - \bar{q}^{2} .$$

With a high mutation rate of µ = 10−5 and an Ne similar to that of some beef cattle populations of 300, e.g. [34, 35], the expected equilibrium frequency is very low, regardless of whether the lethal allele is fully (s = 1) or partially penetrant (s = 0.75): \(\bar{q} \approx 0.0004\) and σ ≈ 0.0031 for a fully penetrant lethal allele, and \(\bar{q} \approx 0.0005\) and σ ≈ 0.0036 for a partially penetrant lethal allele. This analysis clearly shows that there are other forces, i.e., selection, that maintain the high frequency of the three haplotypes.

Economic impact

Analysis of the economic impact of the three haplotypes on the whole Irish beef population supports the role of pleiotropy in maintaining high haplotype frequencies, which should be managed with appropriately optimised breeding programs. The economic impact could be increased if haplotype carriers are identified and mating between carriers is avoided. This is relatively easy to achieve when there is only one or a few haplotypes for which carrier matings are to be avoided. However, if there are many lethal haplotypes to select against, it will be much more difficult to achieve within pure breeds. Crossbreeding could overcome this issue for breed-specific haplotypes.

Genetic causes of lethality and pleiotropy

We found one candidate gene for one haplotype that carries a putatively recessive lethal allele, no candidate genes for another, and several for the third one. ZFAT was the only protein coding gene that overlapped with the AA14H3 haplotype. ZFAT is a transcription factor involved in immune-regulation and apoptosis [36, 37] and plays a role in the development of the hematopoietic system [38]. The Mouse Genome Informatics database reported complete early embryonic lethality for a knock-out allele of ZFAT. ZFAT is also known to be associated with human height [3941] and body size in horses [42]. This is consistent with our results, since we observed an insemination success rate that was 20.2 to 24.2% lower (based on different gestation window size) for the AA14H3 Hh × Hh matings than for the HH × HH matings, and the haplotype was positively associated with weight-related traits and feed intake.

Sixty-four protein coding genes overlapped with the SI16H5 haplotype, of which five SKI, GNB1, ATAD3A ZBTB17, and CASP9 were associated with prenatal or perinatal lethality in the Mouse Genome Informatics database [4347]. This haplotype displays a positive association with feed conversion ratio, which may explain its high frequency in the population.

There were no homozygous individuals for the SI16H5 haplotype, which suggests that the identified haplotype tags the putative recessive lethal allele(s). The existence of homozygous individuals for the AA14H3 and CH19H2 haplotypes suggests that there may be multiple underlying haplotypes with and without lethal allele(s), but we are unable to distinguish them with the current genotyping data. Another possible reason is incomplete penetrance, resulting in some homozygotes not suffering from the deleterious effects of the allele.

Fine-mapping these haplotypes with sequence data could potentially resolve the fine haplotype structure, and identify causal variants for lethality and pleiotropic effects on the selected traits. Efforts to identify such causative variants are ongoing.

Conclusions

We identified three haplotypes, one that carries a putatively recessive lethal allele in Aberdeen Angus and two that carry semi-lethal alleles, one in Charolais and one in Simmental. Carrier matings in Aberdeen Angus and Simmental had a lower success of artificial insemination and a longer interval between insemination and calving. Progeny from carrier matings in Charolais had a higher probability of dying or culling. The haplotype in Aberdeen Angus was in a region that contains the ZFAT gene, which was previously shown to be lethal in mice. The haplotype in Simmental was in a region that contains several candidate genes that potentially cause prenatal or perinatal lethality. Substitution analysis indicated that the haplotypes had pleiotropic effects on the traits under selection. The substitution effects were positive for the terminal index and positive to negative for the replacement index. Further work is needed to identify the underlying causative variants that impact the traits under selection and fitness. Identification of haplotype carriers will improve the breeding success and fitness of beef cattle populations.

Declarations

Authors’ contributions

JJ conceived and designed the study with MM and JMH. GG carried the ideas and interpretation further. JJ performed the analysis. DM prepared phenotypic records. JJ and JMH wrote the first draft. MJ, GG, and JM contributed to the interpretation of the results. All the authors read and approved the final manuscript.

Acknowledgements

Funding for the genotyping of animals used in this study was provided to participants of the Irish Beef Data and Genomics Programme which is a programme funded under Ireland’s Rural Development Programme 2014–2020.

Competing interests

The authors declare that they have no competing interests.

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Authors’ Affiliations

(1)
The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Easter Bush, Midlothian, Scotland, UK
(2)
Irish Cattle Breeding Federation, Bandon, Co. Cork, Ireland
(3)
Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Box 7023, 750 07 Uppsala, Sweden

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